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Sustainable Nanotechnology: Life Cycle Thinking in Gold Nanoparticle Production and
Recycling
Paramjeet Pati
Dissertation submitted to the faculty of the Virginia Polytechnic Institute and State
University in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
In
Civil Engineering
Peter J. Vikesland (Chair)
Sean P. McGinnis (Co-chair)
Linsey C. Marr
Amy Pruden
Scott H. Renneckar
August 4, 2015
Blacksburg, Virginia
Keywords: nanotechnology, LCA, recycling, gold, sustainability
Sustainable Nanotechnology: Life Cycle Thinking in Gold Nanoparticle Production and
Recycling
Paramjeet Pati
ABSTRACT
Nanotechnology has enormous potential to transform a wide variety of sectors, e.g.,
energy, electronics, healthcare, and environmental sustainability. At the same time, there
are concerns about the health and environmental impacts of nanotechnology and
uncertainties about the fate and toxicity of nanomaterials. Life cycle assessment (LCA), a
quantitative framework for evaluating the cumulative environmental impacts associated
with all stages of a material or process, has emerged as a decision-support tool for
analyzing the environmental burdens of nanotechnology. The objective of this research
was to combine laboratory techniques with LCA modeling to reduce the life cycle
impacts of gold nanoparticle (AuNP) production. The LCA studies were focused on three
aspects of AuNP synthesis: 1) the use of bio-based (‘green’) reducing agents; 2) the
potential for recycling gold from nanomaterial waste; and, 3) the reduction of the life
cycle impacts of AuNP production by conducting the synthesis at reduced temperature.
The LCA models developed for AuNPs can inform future nanotechnology-focused LCA
studies. Comparative LCA showed that in some cases, the environmental impacts
associated with green synthesis methods may be worse than those of conventional
synthesis approaches. The main driver of the environmental burdens associated with
AuNP synthesis is the large embodied energy of gold, and so-called green synthesis
methods do not offset those impacts. In addition, the reaction yield, which is seldom
reported in the literature for green synthesis of nanomaterials, was found to greatly
influence the life cycle impacts of AuNP synthesis. Gold from nanomaterial waste was
successfully recovered by using host-guest inclusion complex formation facilitated by -
cyclodextrin. This recycling approach involved room temperature conditions and did not
require the toxic cyanide or mercury commonly used in the selective recovery of gold. A
major advantage offered by this approach for selective gold recovery over conventional
approaches is that the recovery does not involve the use of toxic cyanide or mercury. To
reduce the energy footprint of citrate-reduced AuNP synthesis, the synthesis was
conducted at room temperature. LCA models showed significant reduction in the energy
footprint. The findings of this research can inform future LCAs of other nanomaterials.
iii
DEDICATION
“The greatest obstacle to discovering the shape of the earth, the continents, and the
oceans was not ignorance but the illusion of knowledge.”
-Daniel J. Boorstin
“One accurate measurement is worth a thousand expert opinions.”
-Grace Hopper
“I am recycled cells
I learn to like myself
More with each iteration
I’m an experiment
Each trial is a test
Constant recalibration”
-Sarah Daly (Iterations) Metaphorest
iv
ACKNOWLEDGEMENTS
My Ph.D. journey is dotted with the kindness, support and generosity of several mentors,
colleagues and friends.
I owe my deepest gratitude to Dr. Peter Vikesland, my primary advisor, for his guidance, support
and encouragement throughout my graduate studies at Virginia Tech. Pete: Thanks for pushing
me to strive for high-quality work and for constantly raising the bar. You trusted me when I had
grave doubts about myself and my seemingly insane research plans, and you gave me ample
room to experiment with ideas and to pursue my own intuitions and research interests. I owe
much of my growth as an independent researcher to the fecund research environment, the
generous resources and the numerous opportunities you provided.
Dr. Sean McGinnis, my co-advisor, played a major role in helping me develop my life cycle
thinking muscles and LCA modeling skills. Dr. McGinnis: Our many conversations about
sustainability helped me refine my ideas about the many meanings and interpretations of the
deceptively simple word sustainable. Those conversations also helped me develop a systems
approach for thinking about the wicked complexities at the intersection of environmental
sustainability, economics and ethics. I also appreciate your insights and advice about the nuts and
bolts of teaching.
I would also like to thank my committee members Dr. Linsey Marr, Dr. Amy Pruden and Dr.
Scott Renneckar for their ideas and suggestions, which gave this dissertation its final shape. I
will continue to incorporate your recommendations as I move my research projects forward.
This research would not have been possible without the facilities and resources provided by the
Department of Civil and Environmental Engineering (CEE), the Virginia Tech Center for
Sustainable Nanotechnology (VTSuN), and the Nanoscale Characterization and Fabrication
Laboratory (NCFL). I am especially grateful to Chris Winkler for his many hours of help at the
NCFL. Chris: Thank you for your boatloads of patience, as I tried my inexperienced, shaky, and
over-caffeinated hands at transmission electron microscopy. You made the NCFL inviting and
TEM less frightening – even fun. On behalf of all the eager researchers who show up at the
NCFL with samples, clueless about TEM but reassured that they have Chris to guide them - I
thank you.
I owe a huge thanks to Julie Petruska, for sharing with me her encyclopedic knowledge of lab
protocols and safety practices, and for helping me find obscure chemicals, lab equipment, and
glassware. Julie: Thanks to your help and suggestions in designing experiments that involved
aqua regia, hydrobromic acid and other unsavory chemicals, I successfully managed to not
poison, dissolve or vaporize myself even once.
v
During my Ph.D., I got to work with and to mentor two amazing undergraduate researchers –
Jennifer Kim and Leejoo Wi. Jennifer and Lee: By working with you, I have learnt so much
about mentoring. Your hard work has helped me move multiple research projects forward. I wish
you both the very best.
I was fortunate to be a part of the Environmental Nanoscience and Technology (ENT) Lab. In
my fellow ENTs, I found an incredibly supportive group of friends and colleagues with whom I
shared so many conversations, rants, and laughs.
Andrea: Thank you for all the thought-provoking conversations and brainstorming sessions
about the role of ethics in engineering, the state of academia, the cultural lenses through which
we view life... Thanks also for the aloo paranthas, rice and dal that kept me nourished and alive
when I fell ill before the defense. Bahut bahut dhanyavaad.
Virginia: Thanks to you too for the many conversations and for having me in your team during
the softball matches. With my hand-eye coordination (or lack of thereof), I did not have much to
contribute in terms skills. But I had a lot of fun even as I stayed perpetually confused about the
rules. You bring a special joy, and you should know that everyone in the lab thinks we should
clone you and paradrop your clones all over the globe – the world will be a happier place.
Nina: Thanks for your initiative and commitment to VTSuN. You play multiple roles for
VTSuN - the engine, the steering wheel, the navigation system, and sometimes all three
simultaneously – and make it all seem annoyingly effortless. I am in awe at your efficiency,
creativity, vision and execution, and am always inspired (and very jealous). VTSuN is lucky to
have you.
Weinan: You have taught me so much about lab work, designing experiments, and thinking
through research problems. It was a pleasure working with you and learning from you, and is an
honor to have you as my colleague and friend.
Andrea, Nina, Ron, Matt (Chan), Matt (Hull), Becky, Hossein, Haoran, Marjorie, Virginia, and
Weinan – it was a pleasure.
My project with Sheldon Masters on the role of ethics in environmental engineering education
was one of the highlights of my Ph.D. experience. Sheldon: I could not have done it without
you. Thanks for the many meals, conversations and lightbulb-in-the-head-switching-on
moments.
I would also like to express my gratitude to Matthew Grice in the Graduate School for reviewing
this dissertation draft for formatting issues during one of his busiest times in the year.
vi
No amount of graduate training could have prepared me to handle my arch nemeses that have
always worried, flummoxed and frustrated me – HokieMart and paperwork. I am deeply
indebted to Beth Lucas (EWR) for helping me to navigate the maze of paperwork, solve
fiendishly knotty HokieMart-related puzzles, and for alerting me to upcoming deadlines that
would have blindsided and derailed me. I am also very grateful to Leigh Anne Byrd (formerly in
CEE, currently in Pamplin College) for all her help with scheduling my preliminary and final
exams, and for expediting the paperwork related to those. Beth and Leigh Anne: Thank you so
much for always coming through.
My acceptance into the CEE Ph.D. program at Virginia Tech was made possible by the
education, mentorship and nurturing guidance I received from Dr. Masten at Michigan State
University. Dr. Masten: The lessons I learnt from you at MSU have always stayed with me. Not
only lessons in thinking, reasoning, writing, and scientific rigor, but also lessons in resilience,
kindness and humility that I picked up from you when you not looking, but were busy being
resilient, kind and humble. Forever grateful.
A lot has changed in these last five years. Thankfully, as I made my way through the ebb and
flow of temporary setbacks and lucky breaks, what remained unchanged was the reassuringly
constant love and unwavering support of my family and friends in India. See you all soon.
Virginia Tech has been very kind to me. The chemistry-heavy ENT lab is where I met my wife,
Carol. (What can I say? We literally had chemistry.) I can’t say enough about the support,
encouragement and the tireless cheerleading that Carol provided (teamed up with Lucy, our cat-
like dog). So I won’t. Carol and Lucy: We did it!
param
August 17th
, 2015
vii
TABLE OF CONTENTS
Chapter 1 ------------------------------------------------------------------------------------------------------- 1
Introduction ---------------------------------------------------------------------------------------------------- 1
ATTRIBUTIONS ---------------------------------------------------------------------------------------------------------- 4
COMPLEMENTARY WORK ------------------------------------------------------------------------------------------ 5
REFERENCE --------------------------------------------------------------------------------------------------------------- 7
Chapter 2 ------------------------------------------------------------------------------------------------------ 10
Life cycle assessment of “green” nanoparticle synthesis methods ------------------------------------ 10
ABSTRACT -------------------------------------------------------------------------------------------------------------- 10
INTRODUCTION ------------------------------------------------------------------------------------------------------- 11
MATERIALS AND METHODS ------------------------------------------------------------------------------------- 13
RESULTS ----------------------------------------------------------------------------------------------------------------- 19
DISCUSSION ------------------------------------------------------------------------------------------------------------ 23
SUMMARIES ------------------------------------------------------------------------------------------------------------ 31
ACKNOWLEDGEMENTS ------------------------------------------------------------------------------------------- 32
REFERENCES ----------------------------------------------------------------------------------------------------------- 33
Chapter 3 ------------------------------------------------------------------------------------------------------ 40
Waste Not Want Not: Life Cycle Implications of Gold Recovery and Recycling from Nanowaste
------------------------------------------------------------------------------------------------------------------ 40
ABSTRACT -------------------------------------------------------------------------------------------------------------- 40
INTRODUCTION ------------------------------------------------------------------------------------------------------- 41
MATERIALS AND METHODS ------------------------------------------------------------------------------------- 43
------------------------------------------------------------------------------------------------------------------------------- 45
RESULTS AND DISCUSSION -------------------------------------------------------------------------------------- 45
ACKNOWLEDGEMENTS ------------------------------------------------------------------------------------------- 52
REFERENCES ----------------------------------------------------------------------------------------------------------- 53
Chapter 4 ------------------------------------------------------------------------------------------------------ 57
Bleeding from a Thousand Paper Cuts: Avoiding Dissipative Losses of Critical Elements by
Recycling Nanomaterial Waste Streams ------------------------------------------------------------------ 57
ABSTRACT -------------------------------------------------------------------------------------------------------------- 57
INTRODUCTION ------------------------------------------------------------------------------------------------------- 58
RECYCLING CRITICAL MATERIALS -------------------------------------------------------------------------- 64
viii
CHALLENGES AND CONSIDERATIONS IN RECYCLING NANOWASTE -------------------------- 67
POLICY INNOVATIONS --------------------------------------------------------------------------------------------- 71
REFERENCES ----------------------------------------------------------------------------------------------------------- 73
Chapter 5 ------------------------------------------------------------------------------------------------------ 87
Room Temperature Seed Mediated Growth of Gold Nanoparticles: Mechanistic Investigations
and Life Cycle Assessment --------------------------------------------------------------------------------- 87
ABSTRACT -------------------------------------------------------------------------------------------------------------- 87
INTRODUCTION ------------------------------------------------------------------------------------------------------- 88
MATERIALS AND METHODS ------------------------------------------------------------------------------------- 90
RESULTS AND DISCUSSION -------------------------------------------------------------------------------------- 95
CONCLUSIONS-------------------------------------------------------------------------------------------------------- 113
ACKNOWLEDGEMENTS ------------------------------------------------------------------------------------------ 113
REFERENCES ---------------------------------------------------------------------------------------------------------- 114
Chapter 6 ---------------------------------------------------------------------------------------------------- 121
Summary ----------------------------------------------------------------------------------------------------- 121
REFERENCES ---------------------------------------------------------------------------------------------------------- 125
Appendix A ------------------------------------------------------------------------------------------------- 127
Supplementary materials for Chapter 2 ----------------------------------------------------------------- 127
Life cycle assessment of “green” nanoparticle synthesis methods ---------------------------------- 127
COMPARATIVE LCA OF GREEN AND CONVENTIONAL SYNTHESIS METHODS FOR AuNPs
------------------------------------------------------------------------------------------------------------------------------ 131
AuNP SYNTHESIS USING SPENT COFFEE AND BANANA PEEL EXTRACT --------------------- 133
Appendix B -------------------------------------------------------------------------------------------------- 135
Supplementary materials for Chapter 3 ----------------------------------------------------------------- 135
Waste Not Want Not: Life Cycle Implications of Gold Recovery and Recycling from Nanowaste
---------------------------------------------------------------------------------------------------------------- 135
UNCERTAINTY ANALYSIS IN LCA---------------------------------------------------------------------------- 139
Appendix C -------------------------------------------------------------------------------------------------- 144
Supplementary materials for Chapter 4 ----------------------------------------------------------------- 144
Bleeding from a Thousand Paper Cuts: Avoiding Dissipative Losses of Critical Elements by
Recycling Nanomaterial Waste Streams ---------------------------------------------------------------- 144
REFERENCES ---------------------------------------------------------------------------------------------------------- 148
Appendix D ------------------------------------------------------------------------------------------------- 155
Supplementary materials for Chapter 5 ----------------------------------------------------------------- 155
ix
Seed Mediated Growth of Gold Nanoparticles at Room Temperature: Mechanistic Investigation
and Life Cycle Assessment ------------------------------------------------------------------------------- 155
FORMATION OF GOLD NANOPLATES AND NANORODS --------------------------------------------- 160
UNCERTAINTY ANALYSIS --------------------------------------------------------------------------------------- 166
REFERENCES ---------------------------------------------------------------------------------------------------------- 168
Appendix E -------------------------------------------------------------------------------------------------- 169
Reprint Permission Letters -------------------------------------------------------------------------------- 169
x
LIST OF FIGURES
Figure 2-1 - Life cycle stages of gold nanoparticles. The LCA models include processes from
raw material extraction through nanoparticle synthesis. The impacts of reducing agents are
included in Part I of the study, but excluded in Part II. (Purification steps have been ignored in
all models). .................................................................................................................................... 15
Figure 2-2 - Environmental impacts of 1 mg AuNP synthesis using three conventional reducing
agents (sodium borohydride, citrate and hydrazine) and two plant-derived reducing agents
(soybean seed and sugarbeet pulp). (a) Cumulative energy demands, (b) Climate change
potential and metal depletion potential, (c) Freshwater ecotoxicity and Agricultural land
occupation. The results include the impact of gold salt, reducing agent, deionized water, tap
water, glassware cleaning solvent and energy required for stirring and heating (Part I). Error
bars in represent 95% confidence intervals for the combined uncertainties in the chloroauric acid
and citric acid models, energy use and uncertainties in the EcoInvent unit processes. ................ 21
Figure 2-3 - Cumulative energy demands of 16 different AuNP synthesis methods. The results
include the impact of gold salt, deionized water, tap water, glassware cleaning solvent and
energy required for stirring and heating. The impacts of the reducing agents were excluded in
this calculation (Part II). Error bars in represent 95% confidence intervals for the combined
uncertainties in the chloroauric acid and citric acid models, energy use and uncertainties in the
EcoInvent unit processes............................................................................................................... 23
Figure 3-1 – A (Left) Schematic of the gold recovery and recycling process. B (Right) The
repeating unit involving one [K(OH2)6]+ cation, one [AuBr4]
- anion and two CD molecules. An
additional [AuBr4]- anion is shown to illustrate how the unit is bound to the next unit through
hydrogen bonding. ........................................................................................................................ 45
Figure 3-2 - A (top) Schematic of LCA model for AuNP synthesis and recycling, B (bottom) -
Life cycle impacts of 10%-, 50%-, 90%- and no-recycle scenarios. ............................................ 49
Figure 4-1 - Novel method for recycling indium from secondary sources such as display screens
of used electronics and spent solar cells. Reprinted (adapted) with permission from
Zimmermann, Y.-S.; Niewersch, C.; Lenz, M.; Kül, Z. Z.; Corvini, P. F. X.; Schäffer, A.;
Wintgens, T., Recycling of Indium From CIGS Photovoltaic Cells: Potential of Combining Acid-
xi
Resistant Nanofiltration with Liquid–Liquid Extraction. Environmental Science & Technology
2014. Copyright (2014) American Chemical Society. .................................................................. 64
Figure 4-2 - Lab-on-chip devices as potential sources of recyclable critical materials. These
devices may be discarded after a single use, and hence contribute to dissipative losses if they are
not recycled. This figure shows a paper-based device for colorimetric detection of NADH in a
microliter-scale sample in less than 4 min. The device consists of an upper plastic cover layer
with a hole exposing the test zone, a wax-circled gold nanoparticle (AuNP) coated paper with a
cotton absorbent layer. The detection time was < 4 minutes. Reprinted (adapted) with permission
from Liang, P.; Yu, H.; Guntupalli, B.; Xiao, Y., Paper-Based Device for Rapid Visualization of
NADH Based on Dissolution of Gold Nanoparticles. ACS Appl. Mater. Interfaces 2015.
Copyright (2015) American Chemical Society............................................................................. 66
Figure 4-3 - Material values (y-axis), material mixing (x-axis) and recycling rates (areas of
individual circles) for products. Larger circles imply higher recycling rates. Products with no
circles are assumed to have recycling rates of zero. The material mixing, denoted by H, is the
average number of binary separation steps required to extract any material from the mixture, and
is higher for complex products. As seen from this figure, products with high recycling rates are
clustered in the upper left corner, and the products with the very low recycling rates are in the
lower right. This trend is particularly sharp for products with H > 0.5, where the recycling rates
range from 66 to 96% in the upper left, and from 0 to 11% in the lower right. The authors of the
original work marked the transition zone between them with a line labeled “apparent recycling
boundary”. Similar modeling approaches for nano-enabled products can help in identifying the
more recyclable products. This information can help in making decision when prioritizing the
use of critical materials in specific products. Reprinted (adapted) with permission from Dahmus,
J. B.; Gutowski, T. G., What Gets Recycled: An Information Theory Based Model for Product
Recycling. Environmental Science & Technology 2007. Copyright (2007) American Chemical
Society........................................................................................................................................... 69
Figure 5-1 - TEM micrographs of seed nanoparticles synthesized by (A) pH controlled method
and (B) w/o pH control; (C) TEM size distributions from both methods; (D) Normalized
absorption spectra and hydrodynamic size distribution by intensity (Inset) of two seed
xii
suspensions with (black lines) and w/o pH controlled (red lines) procedures. Suspensions were
diluted 3 and 9 for UV-vis and DLS measurements, respectively. .......................................... 96
Figure 5-2 - TEM images of room temperature seed-mediated AuNPs of different sizes (aspect
ratio): A) 24.0±6.1 nm (AR: 1.15±0.17), B) 37.1±4.6 nm (AR: 1.15±0.11), C) 46.0±4.6 nm (AR:
1.34±0.14), D) 57.6±4.5 nm (AR: 1.14±0.06), E) 69.6±11.8 nm (AR: 1.13±0.07), F) 82.5±14.0
nm (AR: 1.13±0.07), G) 92.4±11.4 nm (AR: 1.15±0.11), H) 100±11.4 nm (AR: 1.11±0.11), I)
111.0±8.3 nm (AR: 1.11±0.09). Inset: histograms of diameters as determined by NIH ImageJ
software. ...................................................................................................................................... 101
Figure 5-3 - Seed mediated growth for AuNPs (C) with mixed solution of HAuCl4 (0.254 mM),
Au seeds (5.35×1010
particle/ml), and Na3Ctr (0.17 mM) at room temperature. TEM images of
particles obtained at different growth times. ............................................................................... 103
Scheme 5-1 - Reactions among Au seeds, citrate and AuCl4- after initial mixing. .................... 106
Figure 5-4 - (A) Size distribution by intensity, (B) mean diameter of peak 1 (located in the range
of 10 – 100 nm in A) and (C) UV-vis absorption spectra obtained at different time stages of seed
growth synthesis of AuNPs. ........................................................................................................ 108
Figure 5-5 – Time-dependent AuIII
and Au level in supernatant by UV-vis (squares) and ICP-MS
(triangles). Inset: corresponding UV absorption spectra. Dash black line is the spectrum of the
initial AuIII solution. Prior to the UV-vis measurement, all AuNP suspensions were diluted 2
with deionized water. .................................................................................................................. 110
Figure 5-6 - SERS spectra of MGITC (20 nM) adsorbed on room temperature and 100 oC seed
mediated AuNPs under 633 nm excitation. MGITC-AuNPs were prepared by quickly adding
1.5 L of 14 M MGITC solution to 1 mL AuNP suspension (5.4×1010
particle/mL). .......... 111
Figure A 1 - The effect of different gold sources on the cumulative energy demand for citrate-
reduced AuNPs. (RoW: Rest of the world. RoW-a: Rest of the world (precious metals from
electronic scrap.) Error bars represent 95% confidence intervals for the combined uncertainties in
the chloroauric acid and citric acid models, energy use and uncertainties in the EcoInvent unit
processes. .................................................................................................................................... 132
Figure A 2 - Heterodispersity in AuNP synthesis using plant-derived chemicals. A) and B)
AuNPs prepared using tea C) AuNPs prepared using coffee and banana peel extract at 80° C. 133
xiii
Figure B 1 - Powder X-ray diffraction of recovered gold. The highlighted peaks correspond to
gold peaks. The unidentified peaks are presumably due to impurities. XRD measurements were
performed on a Rigaku MiniFlex II instrument (Rigaku Americas, The Woodlands, TX, USA).
..................................................................................................................................................... 135
Figure B 2 - UV-vis spectra of recovered gold chloride and chloroauric acid standard. All
measurements were using a Cary 5000 UV-Vis-NIR spectrophotometer (Agilent, Santa Clara,
CA). All samples were scanned in quartz cuvettes (Starna, model# 1-Q-10) with 10 mm path
length........................................................................................................................................... 136
Figure B 3 - Crystal structure information from SAED measurements confirms that the
recovered precipitate is gold. TEM image shows highly aggregated citrate-reduced AuNPs
produced by this approach. The existence of ‘throats’ between individual AuNPs provides
evidence of AuNP coalescence. All TEM and SAED measurements were performed on a JEOL
2100 (JEOL, Peabody, MA, USA) ............................................................................................. 137
Figure B 4 - (Left) The overlapping error bars for 95% confidence intervals should not be
interpreted as statistically insignificant differences, because these LCA models involve
correlated uncertainties. (Right) The majority of the Monte Carlo simulations showed that 90%-
recycle scenario has lower impact than no-recycle scenario in terms of metal depletion, toxicity
and eutrophication. ...................................................................................................................... 140
Figure B 5 - Uncertainty analysis for 90% recycle scenario vs. no-recycle scenario. ............... 141
Figure B 6 - Uncertainty analysis for 50% recycle scenario vs. no-recycle scenario. ............... 142
Figure B 7 - Uncertainty analysis for 10% recycle scenario vs. no-recycle scenario. ............... 143
Figure D 1 - Energy flows (cumulative energy demand) of 1 mg AuNP synthesis at 100 °C.
(Flow lines show individual contributions of different inputs.) ................................................. 157
Figure D 2 - Energy flows (cumulative energy demand) for 1 mg AuNP synthesis at room
temperature. (Flow lines show individual contributions of different inputs.) ............................ 158
Figure D 3 - pH value at room temperature against the concentration ratio of Na3Ctr and AuIII
for a fixed 1 mM AuIII
concentration. ......................................................................................... 159
Figure D 4 - The standard reduction potential (E0) for Au
III Au
0 for the gold solution species
AuClX(OH)4-X (x=0-4). E0 was calculated using the Nernst equation of ∆𝐺0 = −𝑛𝐹𝐸0, where
Gibbs free energy (G0) of AuClX(OH)4-X (x=0-4) was reported by Machesky et al.
1 .............. 160
xiv
Figure D 5 - Seed mediated growth with mixed solution of HAuCl4 (0.254 mM), Au seeds
(3.3×109 particles/mL), and Na3Ctr (0.17 mM) at room temperature. (A) optical images, (B)
absorption spectra and (C) hydrodynamic diameter of growth solutions in different times. ..... 161
Figure D 6 - (A) Size distributions by intensity (DLS) and (B) absorption spectra of a set of
seeded growth prepared samples with increased size and shifted SPR. ..................................... 162
Figure D 7 - UV absorption spectra of [AuCl4]- (0.127mM, black solid line), Na3Ctr (0.088 mM,
red line) and the mixture of same volume of [AuCl4]- and Na3Ctr with final concentrations of
0.127 mM and 0.088 mM respectively (green line). Blue line is expected spectrum for the
mixture based upon the combination of the spectra for [AuCl4]- and Na3Ctr. ........................... 163
Figure D 8 - Comparison of UV absorbance between supernatant from a completely reacted Au
solution and a simulation mixture of HCl and NaCl. The final concentrations of HCl and NaCl
are based on the stoichiometry of equation 11............................................................................ 164
Figure D 9 - TEM images of seed mediated 46 nm AuNPs produced at room temperature (A)
and at 100 oC (B)......................................................................................................................... 165
Figure D 10- Cumulative energy demand (CED), marine eutrophication and water depletion for
1 mg of 46 nm AuNP synthesis at 100 °C vs. room temperature. AuNP synthesis at room
temperature has lower environmental impacts than synthesis under boiling conditions ............ 165
Figure D 11 - The percentage of 1000 Monte Carlo simulations showing that across all impact
categories, most simulations show that the environmental impacts for room temperature AuNP
synthesis are lower than those for synthesis under boiling conditions. ...................................... 167
xv
LIST OF TABLES
Table 2-1- Environmental impacts of three conventional reducing agents (sodium borohydride,
citrate and hydrazine) and two bio-based reducing agents (soybean seed and sugarbeet pulp). The
environmental impacts of unit mass of conventional reducing agents are greater than those of the
plant-derived reducing agents. The impacts of soybean seeds per mg AuNP, however, are greater
than those of the conventional reducing agents. These results highlight that “green” chemicals
can have substantial environmental impacts that may be comparable or even worse than the
impacts of conventional reducing agents. ..................................................................................... 20
Table 2-2 - Challenges in green nano-synthesis and in conducting LCAs for nanotechnologies 28
Table 5-1 - Sizes, concentrations, zeta-potentials, and optical properties of seeded AuNPs ..... 100
Table 5-2 - Cumulative energy demand (CED) for AuNP synthesis at room temperature vs.
boiling conditions. The CEDs for AuNP syntheses at room temperature and under boiling
conditions are 1.25 MJ and 1.54 MJ respectively. ...................................................................... 112
Table A 1 - Environmental impacts across all impact categories for 1 mg AuNP synthesized
using borohydride, citrate, hydrazine, soybean seeds and sugarbeet pulp. (The errors show 95%
interval. The source of the error in each case is the combined effect of the uncertainty due to
energy use and gold salt (chloroauric acid) model.) ................................................................... 128
Table A 2 - AuNP morphology, reaction conditions, CEDs for the different synthesis methods
(assuming 100% reaction yield). ................................................................................................. 129
Table A 3 - AuNP reaction conditions, Freshwater Ecotoxicity and Agricultural Land
Occupation for the different synthesis methods.......................................................................... 130
Table B 1 - Life cycle inventories for custom defined chemicals AuNP synthesis and recovery
steps............................................................................................................................................. 138
Table B 2 - Life cycle inventories for AuNP synthesis steps..................................................... 138
Table B 3 - Life cycle inventories for AuNP recovery steps to treat 1 mg of gold nanowaste .. 139
Table C 1 - Recycling approaches for critical materials ............................................................ 144
Table D 1 - Volumes (V) of nanopure water, HAuCl4, seed suspension, and trisodium citrate
(Ctr) used in the seed-mediated synthesis of the different sized nanoparticles. ......................... 155
Table D 2 - Inputs for 1 mg of the following custom-defined processes in SimaPro: a)
Chloroauric acid, b) Trosodium citrate, and c) AuNP ‘seeds’ .................................................... 156
xvi
Table D 3 - Inputs for 1 mg of seed-mediated, citrate reduced AuNPs synthesized under boiling
conditions .................................................................................................................................... 157
Table D 4 - Inputs for 1 mg of seed-mediated, citrate reduced AuNPs synthesized at room
temperature ................................................................................................................................. 158
Table D 5 - The percentage of nanoplates and nanorods in AuNP sample D – I. ..................... 161
1
Chapter 1
Introduction
In recent years, sustainability has been much discussed by the media, in scientific
communities, by businesses and the general public. The quest for increased energy efficiency
and sustainable use of resources has led to the emergence of promising new developments, one
of which is nanotechnology. The novel properties of nanomaterials have the potential to usher in
transformative technological revolutions. At the same time, there are concerns about the health
and environmental impacts of nanotechnology. Many promising nanotechnologies rely on the
use of high-value, critical raw materials and often involve energy-intensive production processes,
and the use of toxic chemicals. Life cycle assessment (LCA) has emerged as a potential decision-
support tool for analyzing the sustainability of nanotechnology and evaluating the uncertainties
therein.
LCA is a methodological framework for environmental assessment. When used in its
broadest scope, LCA helps in estimating the cradle-to-grave environmental impacts attributable
to the life cycle of a product or process. Environmental assessment within and LCA framework
is done by defining a system boundary for a product or a process, and defining a baseline
(referred to as functional unit) for comparison. For example, in an LCA study for determining
whether glass bottles or aluminum cans would serve as the better packaging material for
beverages, an appropriate functional unit may be liters of the packaged beverage. After defining
the system boundary and functional unit, an inventory of material and energy flows (inputs), as
well as emissions and waste flows (outputs) relevant to the defined system are compiled. All
input and output flows are calculated in relation to the functional unit. Next, the inventory results
2
are aggregated and translated into more environmentally relevant information through life cycle
impact assessment. For example, CO2 emissions are translated into global warming potential.
With regards to impact assessment, it is important to note that converting material and energy
flows (e.g., kg of CO2 emitted or MJ of electrical energy consumed) into relevant environmental
impacts (global warming potential) necessarily involves some weighting. A variety of impacts
such as climate change, stratospheric ozone depletion, smog formation, ecotoxicity,
eutrophication, acidification, resource depletion, water footprint, land use, etc. are considered
under life cycle impacts assessment. LCA has been used in various applications and at a wide
range of scales, (e.g., estimating product footprints in the pulp and paper,1-3
dairy,4,5
meat,6
polymer,7 metal
8 and biofuel
9-11 industries; comparing the environmental impacts of recycling vs.
incineration,12
and; estimating the global warming potentials of using hand dryers vs. paper
towels in restrooms.13
In addition to environmental impacts, LCA framework can also be used to
analyze economic14
and social15,16
aspects of technologies, regulations and policies.
In recent years, LCA has also been used to estimate the environmental impacts of
nanomaterial production, e.g., carbon nanotubes (CNTs),17
starch nanocrystals,18
nanocellulose,19
and silver nanoparticles.20
Several studies have explored the life cycle considerations in the
development of novel nano-enabled products (e.g., clothing21,22
and bandages23
embedded with
silver nanoparticles; lithium-ion batteries containing CNTs;24
and, thin film solar cells employing
nano-crystalline silicon materials).25
Furthermore, life cycle approaches have also been applied
to study the end-of-life treatment of nanomaterials.26-28
The research presented in this dissertation combines LCA modeling with laboratory
techniques to explore the life cycle impacts of gold nanoparticle (AuNP) production and
recycling. Three key aspects of gold nanoparticle (AuNP) synthesis are analyzed from a life
3
cycle perspective: 1) the use of bio-based (‘green’) reducing agents; 2) the potential for recycling
gold from nanomaterial waste; and, 3) the reduction of the life cycle impacts of AuNP
production by conducting the synthesis at reduced temperature.
Chapter 2 is focused on the LCA of ‘green’ synthesis approaches for AuNPs. Several bio-
based chemicals (e.g., extracts from plant leaves) can be used to reduce Au(III) to Au(0) during
AuNP synthesis. These chemicals are milder and less toxic compared to commonly used
conventional (‘synthetic’) reducing agents (e.g., hydrazine or sodium borohydride). Synthesis
methods that employ bio-based chemicals as substitutes for harsher chemicals are often labeled
as green, and are considered to be more sustainable than conventional synthesis approaches.
However, the environmental impacts of the purportedly green methods have not been studied
from a life cycle perspective. A comparative, cradle-to-gate LCA of green vs. conventional
methods for AuNP synthesis is presented in Chapter 2. (The results of this study were published
in Environmental Engineering Science.)29
The results reported in Chapter 2 showed that a substantial portion of the life cycle impacts
of AuNP synthesis are associated with the mining and refining of gold, and substituting toxic
reducing agents (e.g., hydrazine) with bio-based alternatives does not reduce those
environmental impacts. A major hurdle in mitigating the environmental impacts of AuNP
synthesis is tied with the use of gold. One potential solution is to recycle gold from nanomaterial
waste streams. In Chapter 3, a method for selective recovery and recycling of gold from AuNP
waste is presented along with the LCA of the overall process. A manuscript based on this chapter
is currently in preparation.
In addition to gold, several critical materials (e.g., platinum group elements and rare earth
elements) are integral to the development of next-generation nanotechnologies. These critical
4
materials are being increasingly used in a variety of nano-enabled applications, e.g., lab-on-chip
technologies, point-of-care devices and wearable electronics. Without robust strategies to recover
and recycle these resource-limited critical materials from nanomaterial waste streams and
discarded nano-enabled products, dissipative losses from their material flow cycles can pose
supply risks in the future. Chapter 4 reviews the challenges and opportunities regarding the
recycling of critical materials in nanowaste. A manuscript based on this chapter is currently in
preparation.
A third consideration in life cycle issues with AuNP synthesis, besides bio-based reagents
(Chapter 2) and recycling (Chapter 3 and 4), is energy use. One of the most commonly used
AuNP synthesis methods involves the reduction of Au(III) to Au(0) using citrate under boiling
conditions. In Chapter 5, the feasibility of conducting the same synthesis at room temperature
and the potential reductions in life cycle impact are explored. This chapter has been accepted for
publication in Environmental Science: Nano).
The key findings from the studies reported in this dissertation are summarized in Chapter 6.
Additional discussions in Chapter 6 include: limitations in applying the methodology of LCA to
nanotechnology; challenges in choosing a functional unit for comparing nanomaterial production
and the performance of nano-enabled products; uncertainties in the estimates of nanomaterial
production, release and exposure; and lack of nano-specific toxicity information in the life cycle
impact assessment of nanotechnologies.
ATTRIBUTIONS
Dr. Peter Vikesland is the primary research advisor for my research projects and chair of
the Ph.D. dissertation committee. Dr. Vikesland provided guidance for experimental design and
data interpretation related to laboratory studies on AuNP synthesis and gold recycling. Dr.
5
Vikesland also provided valuable suggestions and feedback in the preparation of the manuscripts
presented in the aforementioned chapters.
Dr. Sean McGinnis is the co-advisor for this research and co-chair of the Ph.D. dissertation
committee. Dr. McGinnis provided valuable guidance in developing and trouble-shooting LCA
models, and in preparing the manuscripts presented in Chapters 2, 3 and 4.
Dr. Weinan Leng is the first author for the manuscript on AuNP synthesis at room
temperature (Chapter 5). Dr. Leng designed and conducted all the experiments and developed
much of the original draft for that manuscript. I developed the LCA models and assisted Dr.
Leng in writing and editing the final manuscript for submission. During the peer-review process,
I helped in responding to the reviewers’ comments. I also assisted in the data interpretation,
provided additional supplementary material from the LCA models for the manuscript and helped
in re-drafting substantial portions of the manuscript for resubmission.
COMPLEMENTARY WORK
In addition to the manuscripts included in this dissertation, the results of these research
projects were presented at the conferences listed below. An additional presentation on AuNP
recycling (Chapter 3) and critical material sustainability (Chapter 4) will be presented at the
American Chemical Society’s National Conference in August 2015.
Pati, P., Vikesland, P.J., and McGinnis, S., Precious metal and rare earth element recovery
from waste streams: Technical developments and life cycle considerations of recovering and
recycling gold from nanomaterial waste streams American Chemical Society Fall Meeting,
August 16-20, 2015, Boston, MA (Abstract accepted)
Pati, P., Vikesland, P.J., and McGinnis, S., Sustainable nanotechnology: Life cycle
considerations in green synthesis of nanomaterials and precious metal recovery from
nanomaterial waste streams, Association of Environmental Engineering and Science
Professors (AEESP), June 13-16, 2015, New Haven, CT
6
Pati, P., Vikesland, P.J., and McGinnis, S., Waste Not Want Not: Life Cycle Implications for
Precious Metal Recovery from Nanowaste, International Symposium on Sustainable Systems
and Technology (ISSST), May 18-20, 2015, Dearborn, MI
Pati, P., Vikesland, P.J., and McGinnis, S., Life Cycle Assessment of Cerium Dioxide
Nanoparticle-based Fuel Additives, Sustainable Nanotechnology Organization Conference,
November 2-4, 2014, Boston, MA
Pati, P., Vikesland, P.J., and McGinnis, S., Precious Metal Recovery from Nanowaste for
Sustainable Nanotechnology: Current Challenges and Life Cycle Considerations, Sustainable
Nanotechnology Organization Conference, November 2-4, 2014, Boston, MA
Pati, P., Vikesland, P.J., and McGinnis, S., Life Cycle Assessment of Nanotechnology:
Environmental Impacts of Nanomaterial Production and Precious Metal Recovery from
Nanowaste, American Chemical Society Fall Meeting, August 10-14, 2014, San Francisco,
CA
Pati, P., Vikesland, P.J., and McGinnis, S., Incorporating Life Cycle Thinking into Green
Synthesis of Nanomaterials American Chemical Society Spring Meeting, March 16-20, 2014,
Dallas, TX
Pati, P., Vikesland, P.J., and McGinnis, S., Assessing 'Green' Synthesis Processes for
Nanoparticle Synthesis through a Life Cycle Perspective, Sustainable Nanotechnology
Organization Conference, November 3-5, 2013, Santa Barbara, CA
Pati, P., Vikesland, P.J., and McGinnis, S., Evaluating ‘Green’ Synthesis Processes for
Nanoparticles through a Life Cycle Perspective, American Centre for Life Cycle Assessment
(ACLCA), October 1-3, 2013, Orlando, FL (Poster presentation)
Pati, P., Vikesland, P.J., and McGinnis, S., Gate-to-Gate Life Cycle Assessment of Gold
Nanoparticle Synthesis Process, Sustainable Nanotechnology Organization Conference,
November 4-6, 2012, Arlington, VA
7
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Synthesis Methods. Environmental Engineering Science 2014.
10
Chapter 2
Life cycle assessment of “green” nanoparticle synthesis methods
Paramjeet Pati1,2,3
, Sean McGinnis2,4
, and Peter J. Vikesland1,2,3
*
1Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia
2Virginia Tech Institute of Critical Technology and Applied Science (ICTAS) Sustainable
Nanotechnology Center (VTSuN), Blacksburg, Virginia
3Center for the Environmental Implications of Nanotechnology (CEINT), Duke University,
Durham, North Carolina
4Department of Materials Science and Engineering and Virginia Tech Green Engineering
Program, Virginia Tech, Blacksburg, Virginia
*Corresponding author. Phone: (540) 231-3568, Email: [email protected]
Environmental Engineering Science 31.7 (2014): 410-420
DOI: 10.1089/ees.2013.0444.
Reprinted (adapted) with permission from Mary Ann Liebert, Inc.
ABSTRACT
In recent years, ‘green’ nanomaterial synthesis methods that rely upon natural alternatives to
industrial chemicals have been increasingly studied. Although the feasibility of synthesizing
nanoparticles using phytochemicals, carbohydrates, and other biomolecules is well established,
the environmental burdens of these synthesis processes have not been critically evaluated from a
life cycle perspective. The environmental impacts of nanotechnologies may potentially be
reduced by applying green chemistry principles. However, doing so without evaluating the life
cycle impacts of the processes may be misleading; merely replacing a conventional chemical
with a natural or renewable alternative may not reduce environmental impacts. To explore this
11
issue, we conducted a comparative, screening-level life cycle assessment (LCA) of gold
nanoparticle (AuNP) synthesis using three conventional reducing agents and thirteen green
reducing agents. We found that a substantial portion of the energy footprint of AuNP synthesis is
due to the embodied energy in gold. As a result of this embodied energy, even green AuNP
synthesis methods have significant environmental impacts that are highly dependent upon
reaction times and yields. Our results show that LCA can elucidate the different environmental
impacts of AuNP synthesis processes, help in choosing processes with reduced life cycle impacts
and directing decisions for future research and data collection efforts. We also discuss some
challenges in conducting LCAs for nanotechnologies and highlight some major gaps in the green
nano-synthesis literature that limit the comparability of reported green synthesis protocols. This
research shows that screening-level LCAs can direct nanotechnology research towards more
environmentally sustainable paths.
Keywords: green synthesis, life cycle assessment, sustainability, nanotechnology, gold, LCA,
AuNP
INTRODUCTION
In recent years, the scientific community has focused on the application of nanotechnology
for sustainable development1, energy efficiency
2,3 and effective pollution control and reduction
through the development of novel nano-based environmental monitoring4-6
, environmental
remediation7-9
and numerous other applications. However, the potential for nanotechnology to
address many systemic issues related to global sustainability should be weighed against
uncertainties related to the environmental and health effects of nanomaterials 10
. Nanomaterial
12
syntheses often rely upon multi-step, multi-solvent, manufacturing methods with inherent
sustainability challenges due to their reliance on limited resource materials. Moreover, energy
intensive manufacturing processes11,12
and the potentially hazardous impacts of the
nanomaterials themselves13,14
lead to additional questions about the environmental impacts of
these processes15
.
Gold nanoparticles (AuNPs) are one class of nanomaterial that is receiving significant
attention for their potential capacity to address many societal problems16,17
. A substantial
challenge to the sustainable development of gold-based nanotechnologies is the limited supply of
the raw material. Gold ore grades have declined over the last decade19
, the cost of extracting gold
has steadily increased20
, and there are concerns about having surpassed peak gold21
. The current
demand of gold for nanotechnology-based application may be small compared to other demands
(e.g., jewelry22
). Nonetheless, given the rapid growth of the nanotechnology industry23,24
, the
market share of gold-based nanotechnologies can be expected to increase. It is therefore
important to investigate the efficiencies of the AuNP manufacturing processes that use gold as an
input.
The application of green chemistry principles may potentially help in reducing the
environmental impacts associated with nanotechnology. A common approach towards green
nanotechnology is to use phytochemicals from plant extracts, carbohydrates, and biomolecules as
reducing and capping agents for nanoparticle synthesis (Table 2-1). Throughout this paper we
use the term ‘green’ to refer to the nanoparticle synthesis methods that use plant-derived or bio-
based chemicals. When making the case for plant-derived reducing agents, the intuitive argument
often employed is that natural reductants are less toxic than synthetic ones. However, simply
replacing an industrial chemical with a renewable source may not mitigate the environmental
13
impacts of products that have high embodied energy (e.g., precious metal nanoparticles) or those
that require energy-intensive production processes. The production of plant-derived reducing
agents will require use of fertilizers, pesticides, freshwater, fossil fuels, etc., which can have
significant environmental impacts25,26
. It is therefore prudent to weigh desirable qualities of
renewable chemicals (e.g., increased biodegradability, non-toxicity etc.) against these upstream
impacts, when proposing green nano-synthesis approaches in place of conventional ones. Life
cycle assessment (LCA) is one such quantitative framework that can be used for evaluating the
cumulative environmental impacts associated with all stages of a material – from the extraction
of raw materials through the end-of-life27
.
In this paper, we present a screening-level, comparative LCA of thirteen previously reported
green methods for AuNP synthesis28-39
and three conventional methods that use citrate, sodium
borohydride and hydrazine as reductants40-43
. We also discuss some specific data gaps in extant
green nano-synthesis studies. Lastly, we highlight some of the broader challenges in conducting
LCAs for nanotechnologies.
MATERIALS AND METHODS
We constructed cradle-to-gate AuNP synthesis models using SimaPro (8.0.1) for
comparative LCA of three conventional AuNP synthesis methods and thirteen green synthesis
methods previously described in the peer-reviewed literature. The functional unit used in each of
these LCA models is 1 mg of AuNP synthesized by each method. These LCA models include
processes from raw material extraction and processing through the synthesis of the nanoparticles
(as shown by the dotted box in Figure 2-1). In this study, as discussed later, purification steps
(centrifugation, dialysis, etc.) were excluded. For the purpose of this study, we did not model
14
recycling streams since it is not common practice to capture AuNP waste streams in laboratory
scale synthesis. Waste products from the syntheses were not included in these models since
disposal practices vary widely by lab and location.
AuNPs from citrate reduction (cit-AuNPs) were prepared in the laboratory. The material and
energy inventory for the citrate-based synthesis was characterized using measured data from our
laboratory. These laboratory measurements allow assumptions to be made for the other synthesis
models for which some key inventory information was not available. Cit-AuNPs of 15 nm
diameter were prepared by modifying previously reported synthesis procedures40,41
. In brief, 10
mL of 38.8 mM trisodium citrate (Sigma-Aldrich) was added to 100 mL of 1 mM chloroauric
acid (Sigma-Aldrich) at 100 °C. AuNPs were formed within 1 minute. Boiling was stopped after
5 minutes and the reaction solution was stirred for an additional 10 minutes. The AuNP
suspension was then filtered through a 0.22 μm polytetrafluoroethylene filter and centrifuged in
15 mL Amicon Ultracell-30K centrifuge filters at 5000 × g for 10 minutes (Thermo Scientific
Sorvall Legend X1R). The concentration of remnant dissolved gold ion in the filtrate was
determined by ICP-MS using standard method 3125-B45
as discussed elsewhere 46
. All
experiments were performed in triplicate. The energy required for stirring and heating during cit-
AuNP synthesis was measured using a Watts Up energy meter (Model: PRO).
15
We assumed that the same amounts of tap water, deionized water and cleaning solvents were
used in all synthesis protocols, and based those estimates on the actual amounts required for cit-
AuNP synthesis in the laboratory. These inputs account for a small fraction of the life cycle
impacts of the overall synthesis process, as seen from the results in Table A2 and A3.
Differences in the impacts due to uncertainties in the actual amounts used are likely to be
negligible. The energy requirement inventories were obtained from direct measurements in the
laboratory and information in the peer-reviewed literature about the synthesis methods and
instrument wattage used in the thirteen green synthesis methods. Instrument specifications were
not reported for some processes (e.g., heating and stirring); the energy demands for those
processes were estimated based upon similar measurements for our cit-AuNP production
experiments. (We therefore ignored any differences in the wattage of specific equipment used in
Figure 2-1 - Life cycle stages of gold nanoparticles. The LCA models include processes from raw
material extraction through nanoparticle synthesis. The impacts of reducing agents are included in
Part I of the study, but excluded in Part II. (Purification steps have been ignored in all models).
16
each study). This estimation approach is justified because the bench-top heater and stirrer we
used for the cit-AuNP synthesis process are reasonably representative of the laboratory scale
instruments used by most research laboratories. The average medium-voltage electricity mix for
the US Northeast Power Coordinating Council was used to model energy use. The uncertainty
for energy use was modeled as a uniform distribution with the maximum and minimum values
being ±20% of the calculated energy use as per measurements performed in our laboratory.
The inventory for chemical precursors used in these syntheses was modeled using the
EcoInvent database47
(version 3.01). Because chloroauric acid was not found in any LCA
inventory databases we built a custom-defined ‘chloroauric acid’ (HAuCl4) process in SimaPro
using gold, chlorine, and hydrochloric acid as inputs based on the stoichiometric relation 48
2Au + 3Cl2 + 2HCl 2HAuCl4 (Equation 1)
Similarly, we modeled trisodium citrate as a custom process based on the following equation,
using citric acid and sodium bicarbonate from the EcoInvent 3 database.
C6H8O7 + 3NaHCO3 Na3C6H5O7 + 3H2O +3CO2 (Equation 2)
We assumed a reaction yield of 80% for both equations (1 and 2). In our uncertainty
analysis, we assumed a uniform distribution with a minimum of 70% and a maximum 95%
reaction yield. These assumptions are reasonable based on industrial yield values used to model
chemical processes49
.
Life cycle impact assessment (LCIA) was done using the Cumulative Energy Demand
(CED) method version 1.0847,50
and ReCiPe version 1.0851
. The former method estimates all
embodied and direct energy use for materials and processes in the syntheses to give a detailed
energy footprint across the life cycle. The latter method considers the life cycle impacts across a
17
broader range of environmental impact categories and is an updated method combining the CML
and EcoIndicator assessment methods. The ReCiPe impact assessment was done using midpoints
and the hierarchist (H) perspective with European normalization. All uncertainty analyses were
performed using Monte-Carlo simulations for 2000 runs. The uncertainty analyses include the
uncertainties in the custom-defined chloroauric acid and citric acid, energy use as well as the
uncertainties in the unit processes in EcoInvent used in our LCA models. Further details of the
LCA models and impact assessments are described in Part I and Part II below.
Part I: In the first part of this study, we compared the cradle-to-gate impacts of two green
AuNP synthesis methods (that used soybean seeds and sugarbeet pulp) with three conventional
AuNP synthesis methods (that used citrate, sodium borohydride and hydrazine). Except for
sodium citrate, the remaining four reducing agents were available in the EcoInvent database. For
the LCA models with hydrazine as reductant, the stabilizer poly(vinyl)pyrrolidone was excluded
as it is not available in the LCA databases.
For cit-AuNPs we determined the yield to be >99.9% using ICP-MS. All subsequent
calculations for cit-AuNPs were performed using a reaction yield of 100%. The reaction yields
for sodium borohydride, hydrazine, soybean seed and sugarbeet pulp were assumed to be 100%,
as best case scenarios. The inventory used to compare the five AuNP synthesis methods included
the metal precursor (chloroauric acid), reducing agent, deionized water, tap water, cleaning
solvents and the energy required for heating and stirring. The energy demands for each of the
five syntheses were calculated using the CED impact assessment method. We used the ReCiPe
Midpoint method to investigate how the five different reducing agents affect the environmental
impact of the synthesis process across different impact categories. The results from four impact
categories: i) climate change potential, ii) metal depletion potential, iii) agricultural land
18
occupation, and iv) freshwater ecotoxicity – are presented in Figure 2-2. The results of all
impact categories are tabulated in Table A1. Except for Agricultural Land Occupation, the
environmental impacts associated with our five test reducing agents were found to be at least 10-
2 smaller than the overall impacts of AuNP synthesis. Based upon these findings, we expanded
our study to incorporate other green synthesis approaches, while excluding the reducing agents
from the LCA models, as detailed in Part II of the study.
Part II: In the second part of the study, we performed a comparative LCA study of sixteen
different AuNP synthesis methods, including the five methods analyzed in Part I. The additional
synthesis methods compared in Part II represent a wide variety of green synthesis approaches
and reaction conditions, and are therefore of interest from a comparative LCA standpoint. We
excluded the reducing agents from the inventory, as the plant-derived reducing agents in most of
these studies are not available in the existing LCA databases. As noted previously, the exclusion
of the reductants from the LCA models should have little impact on the final results. The
cumulative energy demands for three different reaction yield scenarios were calculated using the
CED method (Figure 2-3).
The reaction yield for citrate was assumed to be 100% (based on our ICP-MS results). The
reaction yields in the case of sodium borohydride and hydrazine were also assumed to be 100%,
given that they are strong reducing agents. For the green reductants cypress leaf34
and grape
pomace28
, the reaction yields were reported in the literature to be 94% and 80%, respectively.
For the remaining reductants, the reaction yields were not reported and we thus simulated three
different reaction yield scenarios: 50% yield, 75% yield, and 100% yield when calculating the
environmental impacts. These choices for reaction yield scenarios are reasonable based on the
yields for metallic NP synthesis reported in the literature52,53
. The values reported in Table A2
19
and A3 (Appendix A) are based on the best-case scenario (100% yield) for the studies in which
reaction yields were not reported.
RESULTS
Figure 2-2 shows the environmental impacts of production of 1 mg AuNP by different
reducing agents based on the processes modeled in Part I. The purposes of Part I of the study
were to ascertain: i) whether the five reducing agents contributed significantly to the overall
environmental impact of AuNP synthesis, and ii) whether the green synthesis methods (involving
soybean seed and sugarbeet pulp) reduced the overall environmental impacts of the synthesis,
when compared to the processes involving sodium borohydride, citrate and hydrazine. To
facilitate these comparisons, the impacts of the reducing agents alone are presented in Table 2-1.
20
Table 2-1- Environmental impacts of three conventional reducing agents (sodium borohydride, citrate
and hydrazine) and two bio-based reducing agents (soybean seed and sugarbeet pulp). The environmental
impacts of unit mass of conventional reducing agents are greater than those of the plant-derived reducing
agents. The impacts of soybean seeds per mg AuNP, however, are greater than those of the conventional
reducing agents. These results highlight that “green” chemicals can have substantial environmental
impacts that may be comparable or even worse than the impacts of conventional reducing agents.
Environmental impacts of 1 mg of reducing agents
Reducing agent
Cumulativ
e Energy
demand
(MJ)
Climate
change
potential (kg
CO2
equivalent)
Metal
depletion
potential
(kg Fe
equivalent)
Agricultural
land
occupation
(m2.year)
Freshwater
ecotoxicity
(kg 1,4-
dichlorobenzene
equivalent)
sodium
borohydride 4.63 × 10-4
2.87 × 10-5
1.36 × 10-6
5.95 × 10-7
2.49 × 10-9
citrate 3.88 × 10-5
3.40 × 10-6
2.19 × 10-7
6.92 × 10-7
3.03 × 10-9
hydrazine 1.57 × 10-4
1.03 × 10-5
8.49 × 10-7
2.86 × 10-7
1.14 × 10-6
soybean seeds 6.75 × 10-6
8.94 × 10-7
5.03 × 10-8
4.10 × 10-6
2.22 × 10-10
sugarbeet pulp 6.51 × 10-7
4.16 × 10-8
2.64 × 10-9
6.76 × 10-10
6.46 × 10-12
Environmental impacts of reducing agents required per mg of AuNP
Reducing agent
Cumulativ
e Energy
demand
(MJ)
Climate
change
potential (kg
CO2
equivalent)
Metal
depletion
potential
(kg Fe
equivalent)
Agricultural
land
occupation
(m2.year)
Freshwater
ecotoxicity
(kg 1,4-
dichlorobenzene
equivalent)
sodium
borohydride 1.17 × 10-3
7.28 × 10-5
3.46 × 10-6
1.51 × 10-6
6.31 × 10-9
citrate 1.97 × 10-4
3.40 × 10-6
2.19 × 10-7
6.92 × 10-7
3.03 × 10-9
hydrazine 2.56 × 10-5
1.68 × 10-6
1.38 × 10-7
4.65 × 10-8
1.86 × 10-7
soybean seeds 5.59 × 10-5
4.54 × 10-4
2.55 × 10-5
2.08 × 10-3
1.13 × 10-7
sugarbeet pulp 3.43 × 10-3
3.57 × 10-6
2.27 × 10-7
5.81 × 10-8
5.55 × 10-10
21
Figure 2-2 - Environmental impacts of 1 mg
AuNP synthesis using three conventional
reducing agents (sodium borohydride, citrate
and hydrazine) and two plant-derived
reducing agents (soybean seed and sugarbeet
pulp). (a) Cumulative energy demands, (b)
Climate change potential and metal depletion
potential, (c) Freshwater ecotoxicity and
Agricultural land occupation. The results
include the impact of gold salt, reducing
agent, deionized water, tap water, glassware
cleaning solvent and energy required for
stirring and heating (Part I). Error bars in
represent 95% confidence intervals for the
combined uncertainties in the chloroauric
acid and citric acid models, energy use and
uncertainties in the EcoInvent unit processes.
22
Figure 2-2a shows the cumulative energy demand (CED) of the five AuNP synthesis
methods based on the CED impact assessment method. The environmental impacts of the AuNP
synthesis methods across four impact categories (climate change, metal depletion, agricultural
land occupation and freshwater ecotoxicity) are presented in Figures 2-2b and 2-2c. All error
bars in Figures 2-2 and 2-3 represent 95% confidence intervals for the combined uncertainties in
the chloroauric acid and citric acid models (Equation 1 and 2), energy use and uncertainties in
the EcoInvent unit processes.
Plant derived reductants (soybean seeds, sugarbeet pulp) can have environmental impacts
that are one to six orders of magnitude smaller when compared to strong reducing agents
(sodium borohydride, hydrazine; Table 2-1). However, we observe that by substituting
conventional reducing agents with plant derived chemicals, the overall environmental impact of
the AuNP synthesis processes may not be mitigated. Based on the energy requirements for the
laboratory scale synthesis, the cumulative energy demands of AuNP synthesis actually increase
when using green reducing agents (Figure 2-2a).
A key motivation behind the use of plant-derived reductants is to mitigate the toxicity of
conventional reducing agents (such as sodium borohydride or hydrazine). Although some green
reducing agents may be non-toxic compared to stronger, conventional reducing agents, they do
not diminish the overall toxicity when the cradle-to-gate impacts of the AuNPs are considered
(as demonstrated by the freshwater toxicity results in Figure 2-2c). As discussed later, some
environmental impacts may actually worsen when using plant derived reductants (e.g.,
agricultural land use (Figure 2-2c), freshwater eutrophication (Table A2)).
23
The results of Part II of the study are presented in Figure 2-3. Importantly, our LCA
analysis indicates the actual energy footprint for green reducing agents can be even higher than
that for conventional reducing agents if the reaction yields are low. Conducting such LCA
studies requires accurate estimations of reaction yields; it is important to note that reaction yields
are seldom reported in the literature.
DISCUSSION
Comparative Life Cycle Assessment. The motivation for this screening-level, comparative
LCA was to estimate the environmental impacts of AuNPs synthesized through different green
Figure 2-3 - Cumulative energy demands of 16 different AuNP synthesis methods. The results include
the impact of gold salt, deionized water, tap water, glassware cleaning solvent and energy required for
stirring and heating. The impacts of the reducing agents were excluded in this calculation (Part II). Error
bars in represent 95% confidence intervals for the combined uncertainties in the chloroauric acid and
citric acid models, energy use and uncertainties in the EcoInvent unit processes.
24
synthesis methods. Out of potentially 77 different AuNP green synthesis procedures published in
the peer-reviewed literature (Web of Science, 2014), we focused on thirteen studies for our
analysis (Table A2). These studies represent a wide variety of green routes for AuNP synthesis -
using plant extracts29,31,34
, edible food35,37,39
, waste products 28,38
, synthetically prepared purified
reductants (e.g., Vitamin B2, D-glucose)33,36
, as well as processes that used microwave 28
,
sonication 32
. These studies also cover a range of reaction conditions and times.
As mentioned earlier, in Part I of this study, we compared the environmental impacts of
three conventional AuNP synthesis methods with two green synthesis methods for which
inventory data was available in the EcoInvent database. On a unit mass basis, strong reducing
agents (e.g., sodium borohydride and hydrazine) have environmental impacts that are 101-10
6
greater than those of plant-derived reducing agents (Table 2-1). However, as shown in Table 2-
1, Figure 2-2, and Table A1, we find that replacing a toxic reducing agent (e.g., hydrazine) with
a plant-derived reductant may not reduce the environmental impact of the overall synthesis
process. Even in the best case scenario (assumed yield of 100%), the CEDs for green synthesis
methods were higher than for conventional methods due to their longer reaction times, which
required higher energy for stirring (Figure 2-2a). Climate change potentials for the synthesis
methods (Figure 2-2b) followed the same trend as CEDs (Figure 2-2a). This similarity can be
attributed to the fact that greenhouse gas (GHG) emissions are primarily due to fossil fuel use in
upstream processes that are accounted for in the CEDs. Given that 100% reaction yields were
assumed for all five syntheses, the metal depletion potential differed by about 10% (Figure 2-
2b). The impact of a synthesis process on metal depletion potential will typically scale with
reaction yield. In Figure 2-2c, we compare the environmental impacts of toxic reductants
(hydrazine and sodium borohydride) and plant-derived chemicals in terms of freshwater
25
ecotoxicity and agricultural land occupation. Considering that plant-derived reductants are used
to displace toxic reducing agents (e.g., hydrazine), it is interesting to note that the freshwater
toxicity of the soybean seed and sugarbeet pulp methods are only about 10% lower than that of
the hydrazine process. These results show that in some cases, the life cycle impacts of a bio-
based AuNP synthesis method may be comparable to those of toxic chemical-based method.
Thus, while intuitively it may seem that replacing a toxic chemical with a plant-derived chemical
would make a process more benign, the actual gains from this switch may be marginal from a
life cycle perspective. Moreover, this switch may exacerbate the environmental impacts in
another impact category (e.g., agricultural land occupation, Figure 2-2c).
We note that the reducing agents were excluded from the LCA models in Part II. This step
was taken primarily because those chemicals are not available in current LCA databases. We
emphasize, however, that except for Agricultural Land Occupation, the impacts associated with
the reducing agents in Part I were negligible compared to the overall impact of AuNP synthesis.
Therefore, these exclusions are unlikely to change the overall life cycle impacts of the AuNP
syntheses significantly.
A key insight gained from our analysis of the variety of green synthesis approaches in Part II
was that a substantial part of the overall impact of a given synthesis can be associated with
heating, stirring and sonication (Table A2 and A3). Moreover, as shown in Figure 2-3, the CED
of a given synthesis process is strongly dependent on the reaction yield. This calculation
illustrates how a LCA framework can be used to compare the energy footprints of synthesis
processes with reported reaction yields (e.g., grape pomace vs. cypress leaf extract), as well as to
compare bio-based synthesis processes with conventional processes (e.g., citrate reduction).
Reaction yields are seldom reported in the literature. The results in Figure 2-3 highlight the need
26
for reporting reaction yields to facilitate comparison of environmental impacts of nanoparticle
synthesis processes.
A substantial part of the energy footprint in the AuNP synthesis is associated with the use of
gold salt, and is primarily attributed to the mining and refining processes for conversion of bulk
gold from a mineral deposit into gold salt. The energy and environmental impacts of mining and
refining are embedded into most metal-based nanotechnologies and therefore should be
accounted for when referring to a nanomaterial or its application as green. Country-specific and
process-specific differences in mining and refinery of gold also play a role in the overall
environmental impact of gold-based nanotechnologies (Figure A1). Such insight can only be
gained by doing a holistic, life cycle evaluation of purported green nanotechnologies. LCAs can
also help in assessing the environmental impacts and cost-effectiveness of recycling
nanomaterials and nanocomposites that contain precious metals. Additional discussion of the
results from Part II of the study is presented in Appendix A.
Challenges in green synthesis of nanomaterials. Most extant bio-based nanoparticle
syntheses use renewable chemicals and mild reaction conditions. Achieving tightly controlled
nanoparticle synthesis to obtain uniform size and morphology is, however, still a challenge
(Table A2 and Figure A2). A deeper, mechanistic understanding of these synthesis reactions is
required to provide design rules55
for production of tightly controlled sizes and shapes of
nanoparticles and to improve their overall quality56,57
. The extreme variability in the composition
and concentration of phytochemicals in different plant extracts presents another challenge,
making it difficult to establish tightly controlled, reproducible synthesis protocols. Impurities in
bio-based reductants can affect the stability of the surface moieties of AuNPs as well as their
colloidal stability. Heterodispersity in terms of NP size and morphology or colloidal instability
27
can lead to unpredictable and non-ideal properties58,59
and may limit the use of the final products
during the use-phase.
Owing to this heterodispersity, energy-intensive purification steps (e.g., cryo-centrifugation
or ultracentrifugation) may be required after synthesis60
. Post-synthesis purification steps can
increase the environmental impact of the overall synthesis process. Downstream applications
would determine the appropriate purification steps. Since this study is focused on the synthesis
process only, we did not consider purification steps. We note that post-synthesis purification
steps may typically decrease the final AuNP yield, thereby further increasing the environmental
impact of the AuNPs.
Challenges in LCAs of nanotechnologies. Previous studies61-64
identified the lack of nano-
specific characterization factors (CFs) as a major hurdle in conducting LCAs for
nanotechnologies. For example, silver nanoparticles are suggested to be more toxic than AuNPs
65,66 – a crucial property that is not accounted for when estimating life cycle impacts using CEDs
alone. This limitation, however, exists in the case of other impact assessment methods as well.
Because of the lack of scientific data, nano-specific CFs have not been incorporated into the
current impact assessment methods (e.g., Eco-Indicator 99, TRACI 2.0, ReCiPe etc.) that
consider a broader spectrum of environmental impacts. Using impact assessment methods
without nano-specific CFs for LCAs may provide an incomplete picture of the life cycle impacts
of nanomaterials. The challenges in green synthesis of nanomaterials and conducting LCAs of
nanotechnologies are summarized in Table 2-2.
28
Table 2-2 - Challenges in green nano-synthesis and in conducting LCAs for nanotechnologies
Challenges in green nano-synthesis:
If green nanoparticle synthesis protocols are
expected to replace conventional processes
then it must meet the following criteria:
i) Use of benign, sustainably sourced
chemicals (Anastas and Warner, 2000)
ii) Mild reaction conditions (i.e.,
temperatures and pressures close to
ambient) (Anastas and Warner, 2000)
iii) High reaction yields with short reaction
times (Hutchison, 2008)
iv) Tight control of NP size and
morphology
v) The capacity to reproducibly produce
monodisperse, stable nanoparticle
suspensions.
vi) The amenability of the synthesized NPs
for desired surface functionalization
and bio-based applications.
Challenges in nano-LCA:
For life cycle approaches to be embedded into
nano-industries and regulations the following
must be addressed:
i) Building comprehensive life cycle
inventories for nanomaterials (Bauer et
al., 2008; Gavankar et al., 2012).
ii) Establish the actual amounts of
nanomaterial releases (or potential for
release) into different environmental
matrices, pertinent to global and local
environments (Keller and Lazareva,
2013; Keller et al., 2013; Meyer et al.,
2009).
iii) Build consensus-based (Hauschild et
al., 2008), characterization factors
(Bare, 2011; Rosenbaum et al., 2008)
for nano-specific impacts.
iv) Incorporate nano-specific information
into the existing LCIAs and software.
v) Foster industry-government and
industry-academia partnerships to make
confidential business information (CBI)
related to nano-based products easily
accessible for LCAs.
The results presented in Figure 2-3 highlight the importance of yield on the environmental
impact of different synthesis processes. Compared to conventional syntheses that employ strong
reducing agents, green synthesis methods that use milder bio-based reductants may involve
longer reaction times. Reaction yields may also be lower when milder bio-based reductants are
used. Purification steps required for potentially heterodisperse AuNPs synthesized using a
mixture of phytochemicals may further reduce the yield. In such cases, additional steps may be
necessary to improve the reaction yields of green synthesis methods.
29
Although yield influences all environmental impacts of a synthesis process, there are other
factors that should also be considered when choosing the best route for AuNP synthesis.
Colloidal stability, amenability for surface functionalization and future modifications,
monodispersity, tightly tunable size control, biocompatibility – these are all important factors
that should be taken into account when choosing a synthesis process. It may be that a low yield
reaction might actually be better suited for some specific nanomaterial synthesis, based on the
aforementioned criteria. Nonetheless, reaction yields are important when using a high value
synthetic chemical – a purified salt of a precious metal – to make nanoparticles, and should be
calculated when reporting any green synthesis protocol. Although mass does not capture the
properties or the novelty of a new technology and is not based on function, previous studies have
shown that it is useful as a ‘baseline’67-72
. If we know how much of the interim product (e.g.,
AuNPs) needs to be incorporated into a product to achieve a certain function, the results of a
mass-based study can be later converted into a functional unit representative of the application
during the use phase 73
. Based on the scope and objective of this study, a mass-based functional
unit is appropriate 74
.
Challenges in scale-up of laboratory-scale LCAs. The performance of industrial scale
technologies is often more efficient compared to laboratory- or pilot-scale equipment 75
. With
higher reaction yields, recycling of reagents and efficient equipment, the CED for unit mass of
AuNPs produced at the industrial scale may be much lower than those predicted by bench-scale,
screening-level LCAs72
, which may not accurately predict environmental burdens upon scale
up76
. Therefore, the results of our lab-scale study cannot be directly extrapolated to estimate
scaled up impacts. Modeling scale-up scenarios based on laboratory scale studies is likely to
introduce additional uncertainty, especially for emerging technologies77
. Full-scale LCAs are too
30
time- and resource-consumptive to conduct at the research and development stage of novel
products and processes63,78,79
. Instead, by using secondary data and with appropriate assumptions
and sensitivity analysis, screening-level LCAs can highlight the life cycle environmental
impacts, and are therefore more suitable for emerging technologies80
. In the case of nano-
manufacturing, the proprietary nature of the processes and the evolving production
methodologies hinder development of such comprehensive LCAs62,81
. Based on the rapid growth
and proliferation of nanotechnology, it is in the interest of the industry to provide life cycle
inventories. Doing so will help in the development of more robust nano-LCA models and
thereby address concerns of the environmental impacts associated with nano-based products.
Meanwhile, due to the lack of industrial-scale process data, some simplification in nano-LCA
studies is unavoidable82
. Nonetheless, a life cycle approach using laboratory scale studies can
help in decision-directing for future research and data collection68
.
Despite some limitations in the present study as discussed above, our results show that
screening-level LCAs can be a valuable tool for comparing the environmental impacts of
emerging nano-synthesis methods. By incorporating green chemistry concepts as well as life
cycle thinking into nanotechnology, we can usher this rapidly growing field along paths that are
environmentally sustainable rather than those which might inadvertently shift the environmental
burden from one part of the process to another. Using plant-derived chemicals (especially from
plant-based waste or byproducts28,83
) for nanoparticle production and implementing such
processes into industrial-scale nano-manufacturing holds great promise for achieving this goal,
but should be done while considering synthesis efficiencies and overall life cycle impacts.
The results of this study do not suggest that conventional nano-synthesis methods are superior
to green synthesis methods or vice-versa. Indeed, for biomedical applications of AuNPs, plant-
31
derived reactants may be preferred over toxic reductants (e.g., hydrazine or sodium borohydride)
to ensure that the AuNPs are biocompatible. In contrast, for AuNP applications that require
tightly controlled size and morphology, well-established and tunable conventional synthesis
methods may serve better than green methods. Moreover, choosing a particular synthesis method
also requires deliberate value-judgments for assigning weights to different impacts. Which is
more important: freshwater ecotoxicity or agricultural land occupation?
SUMMARIES
The present approach to making nano-synthesis more environmentally benign focuses on
reducing the use of toxic chemicals (e.g., hydrazine) and replacing them with bio-based
chemicals. However, doing so without clear metrics to evaluate the environmental sustainability
of a green synthesis process from an environmental perspective will only provide a partial,
superficial, and at times an ineffective solution to address the complex, ‘wicked’ problems 84
of
sustainability. We therefore need to think about environmental sustainability not just in terms of
renewable inputs and benign processes, but from a broader life-cycle perspective. In this study,
we compared the energy footprint of laboratory-scale green synthesis processes with the
conventional methods, from a life cycle perspective. We found that reaction yield is a key
parameter in determining the CED of a synthesis process, and is especially important in the case
of nanotechnologies based on resource-limited raw materials (e.g., gold). Our results show that
screening-level LCAs of green AuNP synthesis methods are helpful for comparing their
environmental footprints and facilitating decisions regarding environmentally benign synthesis
route. The nanomaterials production industry is still in its infancy; by incorporating life cycle
thinking into nanotechnology, we have the opportunity to proactively direct its future course
along more environmentally sustainable paths.
32
ACKNOWLEDGEMENTS
This material is based upon work supported by the National Science Foundation (NSF) and
the Environmental Protection Agency (EPA) under NSF Cooperative Agreement EF-0830093,
Center for the Environmental Implications of NanoTechnology (CEINT). Additional support
from the Virginia Tech graduate school for P.P. is gratefully acknowledged. Nanoparticle
characterization was conducted using the facilities of the ICTAS Nanoscale Characterization and
Fabrication Laboratory (NCFL). The efforts of Jennifer Kim in the green synthesis of AuNPs,
and Chris Winkler and in the collection of TEM images are much appreciated. We are also
grateful to the three anonymous reviewers who helped us make this manuscript better through
their comments and suggestions.
____________________________
Author Disclosure Statement:
The authors declare no competing financial interests.
33
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40
Chapter 3
Waste Not Want Not: Life Cycle Implications of Gold Recovery and
Recycling from Nanowaste
Paramjeet Pati,1,2,3
Sean McGinnis,2,4
and Peter J. Vikesland1,2,3*
1Civil and Environmental Engineering, Virginia Tech
2Virginia Tech Institute of Critical Technology and Applied Science (ICTAS) Sustainable
Nanotechnology Center (VTSuN)
3Center for the Environmental Implications of Nanotechnology (CEINT), Duke University
4Department of Material Science and Engineering, Virginia Tech
*Corresponding author. Phone: (540) 231-3568, Email: [email protected]
ABSTRACT
Commercial-scale application of nanotechnology is rapidly increasing. Enhanced production
of nanomaterials and nano-enabled products and their resultant disposal lead to concomitant
increases in the volume of nanomaterial wastes (i.e., nanowaste). Many nanotechnologies
employ resource-limited materials, such as precious metals and rare earth elements, which
ultimately end up as nanowaste. To make nanotechnology more sustainable it is essential to
develop strategies to recover high-value, resource-limited materials from nanowaste. To address
this complex issue, we developed laboratory-scale methods to recover nanowaste gold. To this
end, -cyclodextrin facilitated host-guest inclusion complex formation involving second-sphere
coordination of [AuBr4]- and [K(OH2)6]
+ was used for gold recovery and the recovered gold was
then used to produce new nanoparticles. To quantify the environmental impacts of this gold
recycling process we produced life cycle assessments to compare nanoparticulate gold
production scenarios with and without recycling. The LCA results indicate that recovery and
recycling of gold from nanowaste can significantly reduce the environmental impacts of gold
41
nanoparticle synthesis. Besides facilitating gold recovery from nanowaste, this research also has
the potential to improve current waste management practices and inform future nanowaste
management policies.
INTRODUCTION
There has been rapid growth in the number of nanomaterial-based consumer products in
recent years, resulting in a concomitant increase in waste streams containing nanomaterials (e.g.,
nanowaste). Several nanotechnologies depend on resource-limited precious metals and rare earth
elements (REEs). Supply risks related to these critical raw materials will one day threaten the
sustainable growth of nano-industries. In light of the declining global reserves of high-value
metals,1-3
the recovery and recycling of critical materials is of paramount importance. Current
waste treatment practices do not have specific provisions for nanomaterials,4 and uncertainties
regarding end-of-life scenarios currently hinder the formulation of regulations for nanomaterial
waste management and resource recovery from waste streams.5
Conventional metal recovery methods (e.g., solvent extraction,6 ion-exchange,
7 electrolysis,
8
plasma technology,9 and microbiological methods
10,11) offer strategies for recovering high-value
metals and REEs from nanowaste. The diversity and complexity of nanowaste, however, make it
difficult to develop universally applicable methods for waste management.12
Fortunately, recent
studies have developed novel approaches to metal recovery that may address these challenges.
Nano-SnO2 was recovered from industrial electroplating waste sludge using the selective
crystallization and growth of acid-soluble amorphous SnO2 into acid-insoluble SnO2
nanowires13
. In another study, adsorption-induced crystallization of uranium rich nanocrystals
was used for uranyl enrichment.14
Thermo-reversible liquid-liquid phase transition12
and cloud
42
point extraction15-18
also hold promise for the successful separation and recovery of critical, high-
value and resource-limited materials from nanowaste. One such critical raw material is gold.
The concentration of gold in the continental crust is estimated to be about 1.5 µg/kg.19
Gold
ore grades have declined over the last decade;20
the cost of extracting gold has steadily
increased21
and there are concerns about having reached peak gold.22
The current demand for
gold by nanotechnology-based applications is small compared to other demands (e.g., jewelry23
).
Nonetheless, given the rapid growth of the nanotechnology industry,24,25
the market share for
gold-based nanotechnologies is expected to increase exponentially. In the future, a limited supply
of the raw material may pose a substantial challenge to the development of gold-based
nanotechnologies. Therefore, novel approaches for gold recovery from waste streams are being
actively researched today.16,26,27
Recently, Liu et al.26
reported one approach to recover gold
using α-cyclodextrin (α-CD). This method involves the formation of a host-guest inclusion
complex involving tetrabromoaurate anion [AuBr4]-, α-CD, and hexaaquo potassium cation
[K(OH2)6]+, followed by rapid co-precipitation at room temperature. This method has been
reported to have high separation efficiencies (>75%) and recovery yields (> 90%), and unlike
traditional methods for selective gold recovery, does not involve the use of toxic cyanide28
or
mercury.29
In this study, we investigated the applicability of such an approach for the recovery of
gold from nanowaste, and analyzed the life cycle impacts of the process.
Life cycle assessment (LCA) is a quantitative framework used to evaluate the cumulative
environmental impacts associated with all stages of a material – from the extraction of raw
materials (‘cradle’) through the end-of-life (‘grave’).30
Technical innovations that are suggested
to make nanotechnology more sustainable must be analyzed within an LCA framework to
identify potential hidden environmental burdens. For example, the use of benign reagents during
43
nanomaterial synthesis, while intuitively ‘green’, can have significant life cycle impacts.31
Similarly, novel methods for nanowaste recycling may involve hidden environmental costs that
can only be identified through development of comprehensive LCAs. For example, a new
method for recovery of gold from sewage sludge ash was recently reported,27
claiming that the
method “eliminates the need for water” in the recovery process. However, the process involves
temperatures of ~800 °C for optimum gold recovery. High temperature processes typically have
substantial water footprints because they involve considerable fuel consumption and generally
employ high-pressure steam. Any reduction in direct water use during material recovery may be
negated by such indirect water uses. We therefore need to analyze the environmental burdens
from a life cycle perspective when developing new nanowaste management strategies. By
coupling novel recycling approaches with LCA modeling, we can develop next-generation
closed-loop processes for sustainable nanotechnology. For these reasons we conducted an LCA
study for the α-CD-facilitated gold-recovery process and analyzed the life cycle impacts of
different nanowaste recycling scenarios.
MATERIALS AND METHODS
Selective gold recovery by α-CD. We prepared simulated nanowaste comprised of citrate-
reduced gold nanoparticles (AuNPs).32
The simulated nanowaste suspension was precipitated by
adding KCl and was then dissolved using a 3:1 v:v mixture of HBr and HNO3. HBr was
employed to ensure that gold was present as the square planar complex AuBr4-. The pH of the
resultant clear red solution was adjusted to ~5 using KOH. Assuming that all the gold originally
in the AuNP suspension was precipitated and redissolved in the HBr-HNO3 mixture, we added a
calculated mass of α-CD sufficient to achieve a 2:1 molar ratio of gold:α-CD. Almost
44
immediately the clear red solution became turbid. After 30 minutes, the reaction mixture was
filtered through a 0.22 m PTFE filter. The retentate was then resuspended in deionized water by
sonication, which yielded a clear brown solution. An aliquot of 50 mM of sodium metabisulfite
(Na2S2O5) was then added to precipitate and recover gold. The exact volume of 50 mM Na2S2O5
required was based on the amount of gold originally present in the simulated nanowaste. The
percent recovery of gold for three samples was determined by inductively coupled plasma mass
spectrometry (ICP-MS) using standard method 3125-B.33
The solid precipitate obtained after adding Na2S2O5 was recovered by filtration, analyzed
using powder X-ray diffraction (XRD) (Figure B1, Appendix B), and then dissolved in aqua
regia. The yellow solution was boiled to remove HNO3 (observed as brown nitrogen dioxide gas
leaving the flask), while adding HCl intermittently. Boiling was stopped after ebullition of brown
gas concluded. The final solution was analyzed by UV-vis spectroscopy (Figure B2) and used to
synthesize new citrate-reduced AuNPs. The AuNPs were characterized for size and chemical
composition using high resolution transmission electron microscopy (TEM) and selected area
electron diffraction (SAED) (Figure B3). The overall recovery process is summarized in Figure
3-1A.
LCA modeling. We constructed LCA models using SimaPro 8. The functional unit for our
study was 1 mg of AuNP. The inventory for chemical precursors used in the AuNP synthesis and
gold recovery was modeled using the EcoInvent 3.0 database.34
The energy use during AuNP
synthesis and gold recycling was recorded for LCA model development. Energy use uncertainty
was modeled as described elsewhere31
. Life cycle impact assessment (LCIA) was done using the
ReCiPe method35
(version 1.08), using midpoints and the hierarchist (H) perspective with
European normalization. Uncertainty analyses were performed using Monte-Carlo simulations
45
for 1000 runs. Four scenarios were simulated for 0%, 10%, 50%, and 90% recovery of gold from
nanowaste. In these four scenarios, all of the recovered gold was assumed to be recycled to make
new AuNPs, and the unrecovered gold along with other chemicals was simulated as hazardous
waste for incineration. The inventories are presented in Table B1, B2 and B3 (Appendix B).
RESULTS AND DISCUSSION
Selective recovery of gold using α-CD. Host-guest inclusion complexes involving
cyclodextrin (host) and metal ions (guest) have been reported to form rod- and chain-like
nanoscale supramolecular assemblies.36,37
These inclusion complexes form when water
molecules are displaced from the cyclodextrin cavity by more hydrophobic guest molecules, thus
resulting in energetically favorable reduced ring-strain.38
The selective recovery of gold using α-
CD is made possible by the perfect molecular recognition between [AuBr4]- and α-CD, causing
square planar [AuBr4]- to orient axially with respect to the α-CD channel.
26 Moreover, the cavity
between two α-CD molecules is ideally suited to accommodate the octahedral [K(OH2)6]+ ion,
Figure 3-1 – A (Left) Schematic of the gold recovery and recycling process. B (Right) The repeating unit
involving one [K(OH2)6]+ cation, one [AuBr4]
- anion and two CD molecules. An additional [AuBr4]
- anion
is shown to illustrate how the unit is bound to the next unit through hydrogen bonding.
46
thereby restricting its solvation by water molecules in the bulk solution. The specific orientation
of the [AuBr4]- ion and the favorable location of [K(OH2)6]
+ within the α-CD dimer facilitates
second-sphere coordination between [K(OH2)6]+
and [AuBr4]-. A rod-shaped nanostructure forms
due to the equatorial [C–H···Br–Au] hydrogen bonds between α-CD and [AuBr4]-, and axial [O–
H···Br–Au] hydrogen bonds between [K(OH2)6]+
and [AuBr4]-. Individual rods bind to each
other radially due to hydrogen bonding, forming a supramolecular assembly that ultimately
precipitates due to colloidal instability.26
Each unit of this assembly is comprised of an [AuBr4]-
anion and an α-CD dimer enclosing a [K(OH2)6]+
cation (Figure 3-1B).
The superstructure shown in Figure 3-1B does not form in the case of β- or γ-CD due to the
unfavorable cavity size of the CD dimer. The second-sphere coordination is highly specific to
[AuBr4]-. Other gold complexes (e.g., [AuCl4]
-) or square planar anions of other metals, (e.g.,
[PtBr4]- or [PdBr4]
-) cannot form the rod-like assembly.
26 Therefore this method is highly
suitable for selective recovery of gold from mixed nanowaste.
The gold contained within the precipitated superstructure can be isolated by Na2S2O5
reduction. XRD analysis of the reduced precipitate confirmed that it contained gold along with
some unidentified peaks that indicate impurities. UV-vis spectroscopy of this precipitate
following dissolution in aqua regia showed that the absorbance spectrum closely matches that of
chloroauric acid. ICP-MS analysis showed that the percent recoveries of gold for the three
samples were 59.6%, 60.2% and 77.4%. We synthesized citrate-reduced AuNPs using this
recovered gold. The AuNPs were, however, were colloidally unstable and coalesced soon after
synthesis, presumably due to as yet unidentified impurities in the recovered gold. Nonetheless,
the d-spacings in the diffraction patterns confirmed that the nanoparticles were AuNPs (Figure
B3).
47
Nanowaste from laboratories is a complex matrix with extremely low concentrations of
gold. Several parameters need to be precisely controlled for optimum recovery. For example, the
co-precipitation of the rod-like supramolecular assembly is pH-dependent. In the pH range 2.5–
5.9, most of the [AuBr4]-
is bound through complexation and associated with the supramolecular
assembly; the residual concentration of [AuBr4]-
in the reaction mixture is lowest in this pH
range.26
Therefore, the maximum recovery of gold occurs within this pH range. Depending on
the pH (and the residual concentration of [AuBr4]-), the moles of α-CD required for optimum
recovery will vary. Consequently, depending on the concentration of gold recovered in the
resuspended retentate, the moles of Na2S2O5 needed to precipitate and recover gold will also
vary. With this information, the recovery process can be optimized for higher yields and greater
purity of the recovered gold.
LCA of AuNP recycling process. A schematic of the LCA models for this study are shown
in Figure 3-2A. The life cycle impacts of four different gold recycling scenarios (0%, 10%, 50%
and 90% recycling) show that recycling can significantly reduce the environmental impacts of
AuNP synthesis across several impact categories. The normalized impact assessment results
show that the most important impact categories are freshwater and marine eutrophication,
freshwater and marine ecotoxicity, human toxicity and metal depletion. Figure 3-2B shows the
environmental impacts in the categories of metal depletion, freshwater ecotoxicity, human
toxicity and fossil fuel depletion. Scenarios involving recycling outperform the no-recycle
scenario in most cases (as confirmed by uncertainty analysis; Figure B4, B5, B6 and B7), except
for climate change potential, fossil fuel depletion and water depletion. However, based on the
normalized impact assessment results, the environmental burdens of recycle scenarios in these
48
three impact categories were found to be negligible when compared to the benefits of recycling
in other impact categories.
49
Figure 3-2 - A (top) Schematic of LCA model for AuNP synthesis and recycling, B (bottom) - Life cycle impacts of 10%-, 50%-,
90%- and no-recycle scenarios.
50
The high fossil fuel depletion in the recycle scenarios is due to inefficiencies in the
laboratory-scale boil-off of HNO3. Currently, the dissolution of every batch of recovered gold in
aqua regia and subsequent boiling are done in parallel. The energy footprint of this boiling step
can be substantially reduced by first dissolving several batches of recovered gold in aqua regia
and then boiling off HNO3 in a single step. Further analysis of scale-up scenarios may indicate
additional reductions to the energy footprint.
Broader impacts. With increased nanomaterial production, their waste flows will increase as
well, along with the demand for raw materials. A substantial part of the increased raw material
demand can be met by utilizing waste flow streams through closed-loop recycling within nano-
manufacturing infrastructures. Recycling strategies such as the one we present in this paper can
help mitigate the supply risk of critical raw materials in the future.39
Recently there has been a
surge in research on recovery and recycling of precious metals and REEs from anthropogenic
waste streams40
(e.g., cell- phones,41
hard drives,42
printed circuit boards,43
liquid crystal
displays,44
used fluorescent lamps,45
sewage sludge ash27
) as well as the natural environment
(e.g., seawater46
). However, we must analyze recycling approaches from a life cycle perspective
to identify unanticipated environmental burdens. Caballero-Guzman et al.47
reported that current
recycling approaches do not significantly increase the incorporation of recycled nanomaterials in
new products or applications. LCA models can help us analyze how effectively we incorporate
recovered materials into the supply chain. The novelty of our study lies in the combination of
LCA modeling with an innovative approach for selective gold recovery.
As mentioned earlier, the rod-like superstructure involved in the selective recovery of gold
does not form in the case of other square planar tetrahalides (e.g., [PtBr4]- or [PdBr4]
-)26
because
the second-sphere coordination is specific to [AuBr4]-. This method can therefore be applied for
51
selective recovery of gold from mixed nanowaste. Although this study focused on closed-loop
recycling of gold for AuNP synthesis, the separation technique can also be applied for
separation, pre-concentration and open-loop recycling of gold. Moreover using this method, we
can recover gold not only from nanowaste (e.g., nanoparticulate gold in spent point-of-use
sensors and medical devices, bulk gold from e-waste etc.), but also from other waste streams that
contain gold (e.g., e-waste). Given the growing concerns about e-waste management48
and the
urgent need to establish best practices49
, this novel approach for recovering gold is especially
important. By recovering precious metals and REEs from waste streams, we can reduce the
adverse impacts of mining metals and REEs, mitigate the environmental burdens of toxic waste,
decrease the cost of critical raw material procurement and improve the resilience of material
supply chain.50
Current end-of-life treatment facilities may not be well-suited to handle nanowaste, because
nanomaterials may differ significantly in their properties (e.g., specific heat capacities, melting
temperatures etc.) compared to their corresponding bulk materials. For example, current high
temperature metal recovery processes used for battery recycling may be inadequate for nano-
enabled lithium ion batteries. The nanomaterials in those batteries may require smelting
temperatures that are significantly higher than current operating conditions, resulting in higher
energy consumptions and overall emissions.51
In such cases, thermodynamic analysis based on
life cycle approaches can help inform the modifications that current waste management facilities
need to make when dealing with nanowaste. The life cycle considerations highlighted in this
study are therefore integral to the development of future nanowaste management.
To ensure that nanotechnologies based on critical elements are sustainable in the future, we
must incorporate recovery, recycling and life cycle thinking into nano-manufacturing and
52
nanowaste management from inception. Extant environmental regulations, however, do not
address the specific challenges associated with managing nanowaste. There are no well-
established practices for recovery of precious metals in nanowaste generated in laboratories.
Meanwhile, universities and research laboratories rely on in-house policies for collection and
disposal of nanowaste.52
The results of this study are therefore timely, and can address this key
gap in nanowaste management and material recovery, as well as inform future waste
management policies.
ACKNOWLEDGEMENTS
This work was supported by grants from the Virginia Tech Graduate School (Sustainable
Nanotechnology Interdisciplinary Graduate Education Program), the Virginia Tech Institute of
Critical Technology and Applied Science (ICTAS), and NSF Award CBET-1133746.
Nanoparticle characterization was conducted using the facilities of the ICTAS Nanoscale
Characterization and Fabrication Laboratory (NCFL). The efforts of Jennifer Kim and Leejoo Wi
in gold recovery experiments, and Chris Winkler in the collection of TEM images are much
appreciated. We are also grateful to Jeffrey Parks for conducting the ICP-MS analyses.
53
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57
Chapter 4
Bleeding from a Thousand Paper Cuts: Avoiding Dissipative Losses
of Critical Elements by Recycling Nanomaterial Waste Streams
Paramjeet Pati,1,2,3
Sean McGinnis,2,4
and Peter J. Vikesland1,2,3*
1Civil and Environmental Engineering, Virginia Tech
2Virginia Tech Institute of Critical Technology and Applied Science (ICTAS) Sustainable
Nanotechnology Center (VTSuN)
3Center for the Environmental Implications of Nanotechnology (CEINT), Duke University
4Department of Material Science and Engineering, Virginia Tech
*Corresponding author. Phone: (540) 231-3568, Email: [email protected]
ABSTRACT
Critical materials such as precious metals and rare earth elements are integral to the
development of new technologies. However, uncertainties about the future availability of critical
materials raise questions about the sustainable growth and development of promising
technologies. Nanotechnology is one such technology that relies on critical materials.
Commercial-scale applications of nanotechnology are on the rise today. The rapid proliferation
of nanotechnology into electronics, consumer products and lab-on-chip applications suggests that
the demand for critical materials in the nano-manufacturing industry will continue to increase.
Given the potential supply risks associated with critical materials, their recovery from waste
streams is of paramount importance. Without early incorporation of recycling strategies into
nano-manufacturing practices, critical materials in nanomaterial waste streams and discarded
nano-enabled products will result in dissipative losses from the material cycle. It is therefore
essential to develop strategies to recover high-value, resource-limited materials from nanowaste.
In this review, we discuss some key challenges related to recycling; highlight recent
58
developments in selective recovery of precious metals and rare earths; and, identify opportunities
for using waste streams as secondary sources of critical materials.
INTRODUCTION
Critical elements such as noble metals, platinum group elements (PGMs) and rare earth
elements (REEs) wield great influence over societal prosperity and environmental sustainability.
In our interconnected world, a nation’s prosperity depends on successfully developing, adopting
and implementing novel technologies. These technologies in turn are intimately tied to the
reliable supply of several noble metals, PGMs and REEs. Our planet’s endowment of these
critical elements, however, is finite. Uncertainties about their availability loom large as our
desire for sustainable growth and development clashes with the realities of our limited resources
and their unsustainable consumption. A business-as-usual approach threatens the continued
development of next-generation technologies. Nanotechnology is one such promising technology
that strongly depends on high-value, critical elements. Recent studies have estimated dramatic
increases in the demand for REEs required for emerging green technologies.1 Poised today for
exponential growth, nanotechnology’s demand for high purity critical elements will similarly
increase in the near future.
Nanotechnology powered by critical materials. Nanotechnology is an enabling technology
with enormous potential to transform a wide variety of sectors, e.g., energy, electronics,
transportation, healthcare, pharmaceuticals, environmental monitoring, and national security.
Much of the promise of nanotechnology for revolutionary and transformative improvements lies
in the unique properties of critical materials that impart novel optical, photothermal and catalytic
properties2-4
when used as nanoparticles or as dopants in nanocomposites.5-10
For example,
59
nanocomposites comprised of indium oxide nanoparticles and carbon nanotubes showed superior
sensitivity for ammonia gas sensing at room temperature, thus offering an improvement over
conventional ammonia gas sensors, which have limited maximum sensitivity and require high
operating temperatures.11
Besides ammonia, indium oxide nanoparticles can also be used as gas
sensors for carbon monoxide and nitrogen dioxide.12
Terbium-doped CdS and ZnO nanoparticles
have been reported to exhibit enhanced luminescence,10,13,14
and terbium nanoparticles when
used as biolabels for DNA assays, showed a 100-fold increase in detection sensitivity15
. Slow
oxygen reduction reaction (ORR) kinetics on platinum catalysts is currently a key limiting factor
in the energy conversion efficiency of membrane fuel cells.16
Tantalum nanoparticles can help
overcome this limitation as they have been shown to enhance the ORR kinetics.17
Nano-sized yttrium iron garnets (YIG)18
and yttrium aluminum garnets (YAG)19
are used for
developing new magneto-optical devices. Nano-structured palladium- and yttrium-doped ZrO2
electrodes18
have been developed as cathodes of intermediate temperature solid oxide fuel cells
(IT-SOFCs).9 Europium nanoparticles were also used as nano-labels in the successful detection
and bio-imaging of Giardia lambia in environmental water samples.20
Other applications of
critical material-based environmental monitoring tool are thorium-enabled nanocomposites used
in ion-selective membrane electrodes for mercury detection.21
Luminescent properties of
neodymium ion in combination with nanocyrstals (e.g., CaTiO3 nanocrystals22
) hold promise for
advanced photonic applications. Neodymium doped NaYF4 nanoparticles used as optical
temperature sensors.23
Nanoparticles doped with neodymium hold promise as sub-tissue optical
probes because the emission band spectrum of neodymium overlaps with the transparency
windows of human tissues (e.g., neodymium-doped LaF3 core/shell nanoparticles).24
60
The rapid progress made in developing novel nano-enabled devices and their current growth
trends25,26
hint at a future where most of the devices we will have may be in some ways have
enhanced functionality. Be it smarter credit cards,27,28
biometrics,29
batteries,30
light emitting
diodes,31,32
or antimicrobial clothing,33
nanotechnology is poised to permeate every aspect of our
daily lives. Miniaturized, multifunctional, and smart devices with enhanced sensitivity and ultra-
low power consumption will soon find their way into our homes, desks, and pockets. Bottom-up
nano-manufacturing through self-assembly offers unique advantages. Nanoscale memory
architectures based on self-assembly allow for substantial miniaturization in nanoelectronics34,35
due to high packing density and superior performance while consuming less power. Moreover,
these nano-enabled devices themselves may be powered by wearable nanogenerators36
and
human-interactive photodetectors37
made possible by critical materials such as gallium and
indium. Other examples of critical materials in nanotechnologies include europium38
and
yttrium39,40
in anti-reflective displays; silver in photovoltaics,41
photocatalytic systems42
and
organic light emitting diodes;32
samarium and praseodymium in photocatalytic systems;43
gadolinium in multicolor displays;44
ruthenium in solar cells;45-47
gold in nano-enabled
environmental monitoring;48,49
platinum in fuel cells;3,50
palladium in gas sensing;51
gallium in
optoelectronics;52
europium in drug-delivery53
and bio-imaging;7,20
indium in in-vivo bio-
imaging;54
germanium55,56
and tellurium57
in chip-technologies for nanoelectronics; terbium in
bioassays15
and fingerprint detection technologies;58
and dysprosium in white LEDs;59,60
tantalum in biomedical applications;61
and neodymium in permanent magnets,62
optical
temperature sensing23
and sub-tissue thermal imaging.24
Sustainability of nanotechnologies dependent on critical materials. Sustainability has
emerged as a design criterion in nano-manufacturing.63-65
Discussions on the sustainability of
61
nanotechnologies have mostly been focused on environmental implications and applications.
Nanotechnology’s dependence on critical elements and the recycling of noble metals, rare earth
elements and platinum group metals from nanomaterial waste streams has been relatively
underexplored. The realization of nanotechnology’s enormous potential is integrally tied to the
reliable supply of high-purity critical materials in the future. We therefore need rigorous book-
keeping of material flows of critical elements used in various nanotechnologies and quantify the
uncertainties therein.
Combined with the planet’s growing population and the upward mobility and buying power
of consumers, the demand for nano-enabled products and applications will continue to increase.
These factors, combined with the rapid proliferation of nanotechnology into electronics,
consumer products, point-of-care applications in medicine and environmental monitoring etc.
indicate that use for critical materials for the nano-industry will grow rapidly. Dependence on
imports, price fluctuations and supply risks of critical materials will threaten the in-house
development and commercialization of next-generation, transdisciplinary nano-bio-info-cogno
technologies,66,67
as well as the ability to participate in the growing global nanotechnology
economy. Therefore, dynamic material flow analyses of critical materials used in
nanotechnology are urgently required.
Material flows in nanotechnology. The material flows of bulk metals (e.g., lithium,68
aluminum,69,70
nickel,71
copper,72,73
and silver74
) and rare earth elements75
have been reported.
Other studies have focused on material flows related to specific products (e.g., cellphones,76
hard-drives, waste electrical and electronic components (WEEE),77-79
display screens,80
passenger cars81
etc.), Several researchers have raised concerns about the unsustainable use of
metals.82-86
With the declining global reserves of high-value metals,72,87,88
the recovery and
62
recycling of precious metals and rare earth elements is of paramount importance.
Nanotechnology relies heavily on the reliable supplies of critical materials that are limited in
resource and are becoming increasingly difficult to mine. For example, gold ore grades have
declined over the last decade,89
the cost of extracting gold has steadily increased,90
and there are
concerns about having surpassed peak gold.82
Although nanomaterials have been part of
regional and global material cycles for many years, their flows have only recently started to be
quantified.91-99
The initial focus of nanomaterial flows has been on the health and environmental
implications of nanomaterials in treated waste streams, and dissipative losses of critical materials
have not received as much attention. Initial estimations of nanomaterial mass flows involve large
uncertainties and require further research for developing dynamic material flow models, with a
special focus in critical materials. The inventory data for many nanotechnologies is proprietary,
and initial estimates of nanotechnology-related material flows have largely relied on stochastic
analysis and modeling94,99,100
instead of primary (measured) data. Nonetheless, recent studies on
nanomaterial release suggest that residual nanomaterials in the treated waste may be released
into the environment,93,101,102
which might contribute to dissipative losses of critical materials.
Due to the data and knowledge gaps, industries and policy-makers may meet challenges related
to nanomaterial waste flows reactively rather than proactively,103
thus making it difficult to form
long-term policies for producing, trading and recycling critical materials. Determining
nanomaterial waste flows is therefore an urgent research need, especially with regard to
dissipative losses of critical materials.
Nanomaterials may be found in a variety of waste streams, e.g., silver nanoparticles in
wastewater after leaching from antimicrobial textiles,104,105
or carbon nanotubes (in lithium-ion
batteries)106
in battery recycling smelters. Recycling strategies will therefore need to be tailored
63
for specific waste streams and nanomaterials of interest. Before discussing potential recycle
approaches for waste streams containing nanomaterials, it is important to understand that some
waste streams may be more amenable for separation, concentration and recycling than others,
and that information should guide product design to embrace recyclability. For example, TiO2
nanoparticles in toothpaste107
or gold nanoparticles in skin cream108
are likely to contribute
minor dissipative losses109
of titanium and gold from their respective anthropogenic metal
cycles, thus evading recycle. These dissipative losses may be substantial over time because they
will scale with access and buying power of a growing population. On the other hand, critical
materials in some nano-enabled products, e.g., indium tin oxide nanoparticles in display screens
or LEDs31
may be more amenable for selective recovery made possible by pre-processing steps
(i.e., disassembly and separation) followed by selective absorption of indium chloro complex
onto anion exchange resin after acid leaching,110
or by nanofiltration combined with liquid-liquid
extraction (Figure 4-1).111
Although display screens are not designed with easy recyclability of
indium in mind, modular construction of display screens can make separation of parts from used
display screens easier and recovery of indium possible, compared to separating titanium from
used toothpaste. It is also important to note that at the end of the use-phase or during the end-of-
life phase, the critical material in nano-enabled product may no longer be nanoparticulate, and
may no longer exhibit the novel (‘enabling’) properties, and traditional recycling approaches
may be applicable. Nonetheless, a robust quantitative assessment of critical material flows would
help in identifying potential dissipative losses.
64
RECYCLING CRITICAL MATERIALS
In addition to quantifying industry-specific, regional and global flows of critical materials
used in nanotechnology, recovery and recycling strategies must be integrated into nano-
manufacturing from the start. A variety of approaches for recovering critical materials from
conventional waste streams have been reported, which can inform future recycling strategies for
nanomaterial wastes. Examples of critical material recovery include cloud point extraction112
,
selective complexation113, and magnetic recovery
114 (gold); Smopex
® metal scavenging
115,
bioreduction116,117
and biosorption118
(palladium); pyrometallurgical recovery119
and anion
Figure 4-1 - Novel method for recycling indium from secondary sources such as display screens of used
electronics and spent solar cells. Reprinted (adapted) with permission from Zimmermann, Y.-S.;
Niewersch, C.; Lenz, M.; Kül, Z. Z.; Corvini, P. F. X.; Schäffer, A.; Wintgens, T., Recycling of Indium
From CIGS Photovoltaic Cells: Potential of Combining Acid-Resistant Nanofiltration with Liquid–Liquid
Extraction. Environmental Science & Technology 2014. Copyright (2014) American Chemical Society.
65
exchange110
(indium); selective acid leaching followed solvent extraction and precipitation120
(neodymium); hydrometallurgical recovery from waste sludge121
(dysprosium); and selective
extraction using ionic liquids122
(europium). Additional separation and recovery approaches are
listed in Table C1 (Appendix C).
Recent studies have reported novel approaches for recovering high-value materials from
nanomaterial wastes. Nano-SnO2 was selectively recovered from industrial electroplating waste
sludge using the selective crystallization and growth of acid-soluble amorphous SnO2 into acid-
insoluble SnO2 nanowires.123
Adsorption-induced crystallization of uranium rich nanocrystals
was used for uranyl enrichment.124
Thermo-reversible liquid-liquid phase transition125
and cloud
point extraction126-129
also hold promise for the successful separation and recovery of critical
materials from nanowaste. Waste treatment facilities can employ metal detection, sequestration
and removal approaches borrowed from water treatment and environmental contaminant
detection and analysis techniques.126,130-133
Trace metal separation methods can be employed to
recover critical materials using recently reported novel chemistries.113,126,133,134
Pairing these new
recovery approaches with appropriate nanomaterial waste streams can help design anthropogenic
nanomaterial flows with recycling built into the process flow.
An example of future nano-enabled application of critical materials in mass-produced
consumer products is smart clothing.135,136
Wearable technologies that combine electronic
textiles137,138
with wearable nanoelectronics35,56,139
and nanogenerators30,36
can have wide-
ranging applications. Nanopiezoelectronics and sensors140
integrated into smart fabrics can open
up new ways of biomonitoring (e.g., heart rate, electrocardiogram (ECG) measurements,
breathing rates etc.) and replace traditional adhesive based electrodes used in hospitals and
ambulances. Nano-enabled smart fabrics can be used to develop miniaturized, low-cost wearable
66
assistive to technologies for people with
disabilities. Athletic clothing made from e-
textiles and nanoelectronics can be used as
personal fitness trackers. Miniaturization
offered by nanoelectronics can allow for new
ways of integrating wireless communication
devices and audio-video players with smart
fabrics. Given the popularity of consumer
electronics today (e.g., cellphones and MP3
players) it is not difficult to imagine the
potential mass adoption of these wearable
technologies driven by both functionality and
fashion.
Other examples of nano-enabled products
that can be paired with appropriate novel
recycling methods are lab-on-chip141-145
and
point-of-care146-148
devices that rely on critical materials, e.g., gold and silver (Figure 4-2).
These devices may use extremely small amounts of critical materials, but may be mass-produced
and find large-scale applications in diagnostics149,150
and environmental monitoring.48,151,152
When combined with wearable electronics augmented with wireless communication
technologies, these point-of-care devices can assist in early detection and warning of contagious
outbreaks153
. It is important to note that these point-of-care devices might often be discarded
after a single-use. If material recovery is not planned ahead for these devices, they can contribute
Figure 4-2 - Lab-on-chip devices as potential
sources of recyclable critical materials. These
devices may be discarded after a single use, and
hence contribute to dissipative losses if they are not
recycled. This figure shows a paper-based device
for colorimetric detection of NADH in a microliter-
scale sample in less than 4 min. The device consists
of an upper plastic cover layer with a hole exposing
the test zone, a wax-circled gold nanoparticle
(AuNP) coated paper with a cotton absorbent layer.
The detection time was < 4 minutes. Reprinted
(adapted) with permission from Liang, P.; Yu, H.;
Guntupalli, B.; Xiao, Y., Paper-Based Device for
Rapid Visualization of NADH Based on Dissolution
of Gold Nanoparticles. ACS Appl. Mater.
Interfaces 2015. Copyright (2015) American
Chemical Society.
67
substantial dissipative losses over time. Therefore, the disposal of such nano-enabled products
must necessarily involve selective recovery and recycling strategies.
Conventional recycling methods, however, have some drawbacks. For example,
pyrometallurgical methods require high temperatures and are energy-intensive. Similarly,
selective acid leaching and solvent extraction involve strong acids and toxic solvents, generating
large amounts of hazardous chemical wastes which pose substantial health and environmental
risks. Moreover, when applying these recycling approaches to nanomaterial wastes, we face
some unique challenges. The dilute quantities of critical elements and their high degree of
mixing in a complex matrix of different nanomaterial wastes hinder selective recovery and
recycling. Current waste management approaches and treatment facilities may be inadequate for
treating nanowaste, because nanomaterials may have significantly different physicochemical
properties compared to bulk materials. For example, nano-enabled lithium ion batteries may
require much higher smelting temperatures compared to current operating conditions.154
Therefore thermodynamic analyses,154,155
information theory156
and life cycle approaches157
are
needed to inform the modifications that current waste management facilities need to make when
dealing with nanowaste, as well as to inform next-generation waste treatment strategies. Without
proper analysis of the life cycle and thermodynamic considerations, recovery approaches may
not significantly increase the incorporation of recycled nanomaterials in new products or
applications.102
CHALLENGES AND CONSIDERATIONS IN RECYCLING NANOWASTE
When developing recycling strategies for nanomaterial waste streams, it is important to note
recyclability has not been a core focus of product design paradigms. In fact, product design has
increasingly shifted towards using less recyclable materials.156
Three key factors make recycling
68
critical elements from nanomaterial waste streams challenging: high degree of mixing,
miniaturization and dilution. For recycling to be profitable, the financial gains from obtaining the
recycled material should exceed the cost of interim steps (separation, collection, processing).
Modern products have a higher degree of mixing of critical raw materials, making separation
increasingly difficult (Figure 4-3), thereby raising the cost of these interim steps.
Miniaturization of modern products (e.g., laptop computers) also decreases the value of the
recycled material per unit (i.e., per laptop),156
which further diminishes the economic incentives
for recycling. Also, critical materials may form a small fraction of the overall nanomaterial waste
stream, and from a thermodynamic standpoint, the work required to separate a critical material
from a mixture monotonically increases as the mixture becomes more dilute.155
These three
factors (i.e., degree of mixing, miniaturization, and dilution) must therefore be considered when
developing strategies and policies for recycling nanomaterial waste streams.
69
Figure 4-3 - Material values (y-axis), material mixing (x-axis) and recycling rates (areas of individual circles)
for products. Larger circles imply higher recycling rates. Products with no circles are assumed to have
recycling rates of zero. The material mixing, denoted by H, is the average number of binary separation steps
required to extract any material from the mixture, and is higher for complex products. As seen from this
figure, products with high recycling rates are clustered in the upper left corner, and the products with the very
low recycling rates are in the lower right. This trend is particularly sharp for products with H > 0.5, where the
recycling rates range from 66 to 96% in the upper left, and from 0 to 11% in the lower right. The authors of
the original work marked the transition zone between them with a line labeled “apparent recycling boundary”.
Similar modeling approaches for nano-enabled products can help in identifying the more recyclable products.
This information can help in making decision when prioritizing the use of critical materials in specific
products. Reprinted (adapted) with permission from Dahmus, J. B.; Gutowski, T. G., What Gets Recycled: An
Information Theory Based Model for Product Recycling. Environmental Science & Technology 2007.
Copyright (2007) American Chemical Society.
70
The heterogeneity of waste containing nano-enabled products is another complication.
Material flows interweave. The mining, refining and recycling of earth-abundant metals, noble
metals, platinum group metals and rare earths are interconnected, and the challenges in their
production and recycling cannot be considered independently of each other158
. Similarly, in the
case of nano-enabled products, critical elements may be considered as co-products or even
impurities if the recycling is focused on extracting other components in the waste mixture. For
example, in the case of smart clothing, the nanoelectronics can hinder the recyclability of the
textiles138
by being dispersed as a contaminant in the heterogeneous mixture. Nonetheless,
innovations in separation techniques in the end-of-life phase of nano-enabled products can help
circumvent this issue.159
Intersecting and interwoven material flows must be taken into account when making
decisions for implementing recycling strategies for nanowaste. As mentioned earlier, data gaps
and uncertainties can make such decision-making reactive instead of proactive. To inform
decisions on recycling, a key research need is to develop dynamic material flow models73
for
individual materials as well as for specific technologies.88
Such models will help identify
intentional sinks (e.g., landfills) of critical materials used in nanotechnology and unintentional
dissipative releases (e.g., residuals released during incineration), and will link those
anthropogenic material flows with natural cycles when possible. Knowledge of such material
flows will aid in choosing current environmental and anthropogenic sinks that can best serve as
secondary sources of critical materials.71
In addition to the novel recycling methods mentioned earlier, another technological solution
for reducing nanotechnology’s dependence on critical materials is to find substitutes. For
example, carbon nanotubes and silver nanowires hold promise as potential substitutes for indium
71
tin oxide, which is widely used in touch screens. Other efforts to seek alternatives include the
Heusler Alloy Replacement for Iridium (HARFIR) initiative160
, Recyval-Nano161
and
NOVACAM162
. Substitution strategies, however, have limits163
at least in the short-to-medium
term. Current efforts to substitute critical materials with more earth-abundant alternatives or
renewable materials hold promise for the future. In the meantime, however, we will continue to
rely on critical materials to allow the novel substitution technologies to mature.
POLICY INNOVATIONS
In addition to technological solutions, we need proactive policy innovations to ensure that
critical material-dependent nanotechnologies are sustainable. Extended producer responsibility
for several consumer products and landfill bans for electronic waste are examples successful
policies that favor recycling. Policy measures can also help set up material flow cycles that keep
critical elements in circulation within specific nanotechnology-based industries or economies,
e.g., platinum leasing programs for fuel cells.164
Policies must also ensure that critical materials
are employed for critical needs, and for uses that are most the amenable for recycling. For
example, knowing that gold, silver, and platinum are scarce elements, is it justified to use these
critical materials in cosmetics?108,165
Finally, policy-makers should also identify latent demand
for nano-enabled products and services, and safeguard against potential macroeconomic rebound
effects that may undermine the sustainability of critical elements despite increases in material
use efficiency.166
As we begin searching our seas,167
ocean floors,168
and neighboring asteroids169-171
for
critical materials, it is important that we also avoid losing them via unintentional and avoidable
dissipative routes. A close scrutiny of innovation trends and technological developments will
help in identifying how to best integrate waste preventative strategies at this early phase of
72
nanotechnology. Current product design practices, consumer behavior, inadequate recycling
technologies and the limitations on separation imposed by thermodynamics contribute to low
rates of recycling.172,173
In addition, low recycling rates of critical materials have been attributed
to high dissipative losses along their life cycle,174
during which they can be lost in use phase and
may get mixed with other material flows, which can make separation and recovery difficult.
Such dissipative losses in recycling have been identified before,175,176
but recycling
nanomaterials presents new challenges.154,172,177
Policy innovations, recycle-friendly product
designs, novel methods for recycling combined with dynamic material flow analyses,
thermodynamic modeling and life cycle assessments can help in minimizing dissipative losses of
critical materials used in nanotechnologies. To effectively tackle the challenges in recycling
critical materials from nanomaterial waste, technological innovations must be complemented
with appropriate environmental and societal metrics, market strategies, economic incentives and
novel entrepreneurial initiatives. It is therefore necessary to address these issues through an
interdisciplinary framework, global stewardship efforts and a collective vision.
73
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Chapter 5
Room Temperature Seed Mediated Growth of Gold Nanoparticles:
Mechanistic Investigations and Life Cycle Assessment
Weinan Leng, Paramjeet Pati, and Peter J Vikesland *
Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State
University, 418 Durham Hall, Blacksburg, VA 24060-0246
*Corresponding author e-mail address: [email protected]
(Room Temperature Seed Mediated Growth of Gold Nanoparticles: Mechanistic
Investigations and Life Cycle Assessment)
Weinan Leng, Paramjeet Pati and Peter Vikesland, Environ. Sci.: Nano, 2015,
DOI: 10.1039/C5EN00026B
Adapted from Environmental Science: Nano with permission from The Royal Society of
Chemistry)
ABSTRACT
In this study, we report the first room temperature seed-mediated synthesis of gold
nanoparticles (AuNPs) in the presence of citrate and gold salt. In contrast to citrate-reduction in
boiling water, these mild reaction conditions provide expanded capacity to probe the mechanism
of seed-mediated growth following gold salt addition. Moreover, comparative life cycle
assessment indicates significant reductions in the environmental impacts for the room
temperature synthesis. For this study, highly uniform gold seeds with Z-average diameter of 17.7
± 0.8 nm and a polydispersity index of 0.03 ± 0.01 were prepared by a pH controlled protocol.
We investigated the AuNP growth mechanism via time resolved UV–vis spectroscopy, dynamic
light scattering, and transmission electron microscopy. This study indicates that citrate and its
oxidation byproduct acetone dicarboxylate serve to bridge and gather Au(III) ions around gold
nanoparticle seeds in the initial growth step.
88
INTRODUCTION
Nanotechnology holds immense promise for its capacity to address many societal problems.
A key challenge in exploiting the novel properties of nanomaterials is in the synthesis of
nanoparticles with precisely controlled sizes and morphologies. In addition, nanomaterial
synthesis may involve multi-step, multi-solvent, energy intensive manufacturing processes1, 2
which may be associated with significant environmental impacts. Recently there have been
increased efforts 1) to develop design principles to synthesize highly monodisperse
nanoparticles3, 4
and 2) to incorporate the principles of green chemistry into nanomaterial
synthesis.5-7
In this paper we present a novel approach for the seeded growth of gold
nanoparticles (AuNPs) at room temperature and compare its life cycle impacts with those of
previously reported methods8, 9
that require high-temperature boiling.
AuNPs and their conjugates are particularly versatile nanomaterials.10-12
Exhibiting low
toxicity in biological systems,13-15
AuNPs conjugated with drugs and peptides have been used to
modulate pharmacokinetics and drug delivery, thus allowing for specific targeting of cancer cells
and organelles.16-21
The physical properties of AuNPs (e.g., color, localized surface plasmon
resonance (LSPR), electrical conductivity, etc.) are significantly enhanced when they are
functionalized with appropriate metal or organic groups.22
For example, aggregation induced
changes in plasmon response can be coupled with colorimetric detection mechanisms to establish
rapid analyte detection.13, 23-27
Such methods are promising in that they entail very simple sample
handling procedures, minimum instrumental investment, and can be carried out in the field using
portable devices.
The nanoscale properties of AuNPs are size- and shape-dependent,11, 28
and thus there has
been an extensive effort to control AuNP size, shape, and surface composition while
89
simultaneously maintaining narrow size distributions.11, 29-32
The synthesis of gold nanoparticles
by trisodium citrate (Na3Ctr) mediated reduction of aqueous chloroauric acid (HAuCl4)8, 9
, is one
of the most widely used AuNP synthesis strategies. This synthesis approach, involving rapid
addition of Na3Ctr into a hot aqueous solution of HAuCl4, has been modified and optimized over
many decades.31, 33-35
In this synthesis Na3Ctr simultaneously acts as (i) reducing agent (driving
the reduction of AuIII
to Au0),
9, 33, 36, 37 (ii) capping agent (electrostatically stabilizing the AuNP
colloidal solution),37-39
and (iii) pH mediator (modifying the reactivity of Au species involved in
the reaction).31
Room temperature syntheses of noble metal nanoparticles involving synthetic surfactant40
and bio-based reductants and capping agents41
have been previously reported. Seed-mediated
growth of AuNPs has been shown to be especially effective in producing highly monodisperse
AuNPs42, 43
. In this work, however, we discuss what we believe to be the first effort to examine
seed-mediated AuNP growth in the presence of citrate and gold salt at room temperature. Highly
uniform and reproducible gold seeds were prepared for seed-mediated growth using a pH-
controlled protocol. By inoculating the growth medium with a controlled number of gold seeds,
the particles produced via this approach have sizes varying from 20-110 nm with the final size
dependent on the number of seeds and the total concentration of gold ions in the growth solution.
Given the room temperature conditions, this seeded growth synthesis approach adheres to
Principle 6 of the Green Chemistry Principles44
(Design for Energy Efficiency), which
recommends using ambient temperature and pressure when possible. The longer reaction times
also offer new opportunities to probe the reaction mechanism and study the evolution of AuNP
size and morphology.
90
Sustainability has been identified as an emerging design criterion in nanomaterial synthesis.3
Incorporating green chemistry and engineering principles into nanoscience has been suggested as
a proactive approach to mitigate the environmental impacts of nanotechnology.5, 6
However,
green synthesis approaches for nanoparticle production may have unintended environmental
impacts.45
Life cycle assessment (LCA) is being increasingly used to study the environmental
impacts of different nanotechnologies46-50
to assess tradeoffs and identify environmental hotspots
therein. For example, are reductions in the energy footprint of the AuNP synthesis process due to
the milder room temperature conditions substantially larger than any increase in the energy use
due to longer reaction times? To investigate this issue, we conducted an LCA study to compare
the environmental impacts of the AuNP synthesis at room temperature as well as under boiling
conditions.
MATERIALS AND METHODS
Materials. Gold(III) chloride trihydrate (HAuCl4·3H2O) and trisodium citrate dihydrate
(Na3Ctr·2H2O) were purchased from Sigma-Aldrich (St. Louis, MO) at the highest purity grade
available. Deionized water (18 MΩ-cm) was used for all preparations. All glassware was cleaned
in a bath of freshly prepared aqua regia (HCl/HNO3, 3:1 v/v) and then rinsed thoroughly with
deionized water prior to use. All reagent solutions were filtered through a 0.2 μm polycarbonate
membrane prior to their use in AuNP synthesis.
AuNP seed preparation. Gold nanoparticles of 14 nm diameter were synthesized
according to Frens et al.8 with a slight modification for size and monodispersity control.
31 This
synthesis involves chemical reduction of AuCl4- at pH 6.2−6.5 by dissolved Na3Ctr at 100 °C. In
brief, 100 mL of 1 mM HAuCl4 containing 200 µL of 1 M NaOH was prepared in a 250-mL
91
flask equipped with a condenser. The solution was brought to boil while being stirred with a
PTFE-coated magnetic stir-bar and 10 mL of 38.8 mM Na3Ctr was rapidly added. The reaction
was allowed to proceed until the solution attained a wine red color. After 15 min of reaction, the
reflux system was shut down and deionized water was added to the AuNP seed suspension to
bring the final volume to 100 mL. ‘Room temperature synthesis’ refers to seed-mediated
growth of AuNPs, and not the synthesis of AuNP seeds. We note that citrate-stabilized AuNP
seeds may be synthesized by other methods that may or may not involve elevated temperatures.
Seed-mediated AuNP growth at room temperature. Growth reactions (40 mL final volume)
were performed in a 100-mL Erlenmeyer flask. Briefly, a variable volume aliquot of seed
suspension (N = 6.54 1012
particles/mL) and 227 µL of 44.7 mM HAuCl4·3H2O were added to
the flask with water. Subsequently, a 176 µL aliquot of 38.8 mM Na3Ctr·2H2O was added to the
flask under constant stirring. In these syntheses the only variable was the initial AuNP seed
concentration (Table D1, Appendix D).
AuNP characterization. UV–vis spectra were acquired using a Cary 5000 UV-vis-NIR
spectrophotometer. AuNP suspensions were placed in 1 cm sample cells and spectra between
400-800 nm were acquired at room temperature. For the time-dependent measurements of the
seeded growth experiments, solutions were removed and samples were probed within 2 min of
reductant addition. At the same time, an aliquot of suspension was frozen at -20 C. At this
temperature the suspended nanoparticles precipitated out of the suspension. The thawed solution
was centrifuged at 10000 g for 10 min, and the supernatant was used for UV-vis and ICP-MS
analysis.
Gold nanoparticles were visualized using a Zeiss 10CA transmission electron microscope
equipped with an AMT Advantage GR/HR-B CCD Camera System. Sample aliquots of 3 μL
92
were drop-cast onto carbon-coated 100-mesh copper grids (Electron Microscopy Sciences. After
5 minutes, the drop was wicked away using filter paper. The sample was rinsed three times by
inverting the TEM grid onto a drop of water and left in contact with water for 5 seconds, finally
allow the grid to dry face up. TEM images of the as prepared AuNPs were used for size
distribution measurements. For each sample, the dimensions of >60 particles were quantified
using NIH ImageJ software (version 1.44). Electrophoretic mobility and intensity based particle
size distributions and hydrodynamic diameter were determined with a Zetasizer NanoZS
instrument (Malvern Instruments, UK) with a 173° scattering angle at a temperature of 25 °C. A
refractive index of 1.35 and an absorption value of 0.01 were used for the AuNPs.51
Raman
experiments were performed using a WITec alpha500R (Ulm, Germany). A 10× Olympus
objective (NA=0.3) was used to focus a 633 nm laser into a 2-mm flow cell. The Raman signal
was collected in 5 minutes with 30s of integration time.
Size and concentration calculation of AuNPs. (1) Size and concentration of Au seeds. The
average size of the gold seeds was calculated via TEM analysis. A TEM image of seeds
synthesized via the pH controlled method is shown in Figure 5-1. Using ImageJ software, the
average nanoparticle diameter (dseed) was determined to be 13.9 ± 0.5 nm. Assuming a spherical
particle and a reaction yield of 100%,45
the number density of gold seeds (Nseed = 6.75×1012
particles/mL) was calculated based upon the known initial concentration of gold cAu (mol/L):52
𝑁𝑠𝑒𝑒𝑑 =6×1021𝐶𝐴𝑢𝑀
𝜋𝜌𝐴𝑢𝑑𝑠𝑒𝑒𝑑3 (1)
where ρ is the density for gold (19.3 g/cm3) and M is the atomic weight of gold (197 g/mol). A
similar concentration of 6.54×1012
particles/mL was calculated based upon the absorbance of the
particle suspension at 450 nm (A450) using the method reported by Haiss et al.53
93
𝑁𝑠𝑒𝑒𝑑 =𝐴450×10
14
𝑑𝑠𝑒𝑒𝑑2[−0.295+1.36exp(−(
𝑑𝑠𝑒𝑒𝑑−96.8
78.2)2
)]
(2)
Given the similarity of these values and due to the possibility of overestimating the gold
nanoparticle concentration following filtration, a Nseed value of 6.54×1012
particles/mL as
determined using the Haiss equation was used in all calculations.
(2) Size and concentration of seed mediated AuNPs.
Assuming that (a) all of the gold precursor is consumed during the reaction, (b) the resultant
AuNPs are spherical in shape, and (c) gold reduction and nanoparticle growth take place without
nucleation of new ‘seed’ particles, the effective size of the grown particles can be quantitatively
predicted.54
𝑑𝐴𝑢𝑁𝑃3 = 𝑑𝑠𝑒𝑒𝑑
3 +6×1021𝑚𝐴𝑢
𝜋𝜌𝐴𝑢𝑛𝑠𝑒𝑒𝑑 (3)
Where mAu and nseed are the Au mass (g) and the number of seed particles present during seed
mediated growth. The number density of AuNPs (NAuNP) is simply nseed divided by the total
volume (V) of the AuNP solution,
𝑁𝐴𝑢𝑁𝑃 =𝑛𝑠𝑒𝑒𝑑
𝑉 (4)
The molar concentration of the AuNP solutions was then calculated by dividing the number
density of particles by Avogadro's constant (6.022×1023
).
Life cycle assessment (LCA) of AuNP synthesis methods. LCA is a quantitative framework
used to evaluate the cumulative environmental impacts associated with all stages of a material –
from raw material extraction through the end-of-life.55
We conducted a cradle-to-gate
comparative LCA of seeded-AuNP growth at room temperature and under boiling conditions.
Our LCA models consider processes from raw material extraction (“cradle”) and processing
through the synthesis of the nanoparticles (“gate”). The functional unit is 1 mg of AuNP
synthesized by each approach. The LCA models exclude purification steps and synthesis waste
94
products. Furthermore, we did not consider recycle streams since it is not common practice to
capture AuNP waste streams in laboratory scale synthesis.
The material and energy inventories for the AuNP synthesis were built using measured data
from our laboratory. The average medium-voltage electricity mix for the US Northeast Power
Coordinating Council was used to model energy use. The uncertainty for energy use was
modeled as a uniform distribution with the maximum and minimum values being ±20% of the
calculated energy use as per measurements performed in our laboratory. LCA models were
constructed using SimaPro (version 8.0.4). The inventory for chemical precursors used in these
syntheses was modeled using the EcoInvent database56
(version 3.01).
Gold(III) chloride and sodium citrate were not found in the LCA inventory databases.
Therefore, the synthesis of these two chemicals were modeled as custom-built processes using
appropriate assumptions for yield and uncertainties as discussed elsewhere.57
Life cycle impact
assessment (LCIA) was done using the Cumulative Energy Demand (CED) method56, 58
(version
1.09) and the ReCiPe MidPoint method (version 1.11), using midpoints and the hierarchist (H)
perspective with European normalization. CED estimates the embodied and direct energy use for
materials and processes in the syntheses and gives a detailed energy footprint. The ReCiPe
impact assessment method estimates life cycle impacts across a broad range of impact categories
(e.g., climate change, freshwater eutrophication, marine ecotoxicity, etc.). All uncertainty
analyses were performed using Monte-Carlo simulations for 1000 runs. The uncertainty analyses
include the uncertainties in the custom-defined processes in SimaPro, energy use in lab
equipment and the unit processes in EcoInvent used in our LCA models. Figures D1 and D2
show the chemicals and processes considered in the LCA models. The life cycle inventories are
shown in Table D2, D3 and D4.
95
RESULTS AND DISCUSSION
Monodisperse AuNP seed production. Highly uniform and reproducible AuNP seeds were
prepared via citrate reduction both with and without pH adjustment. In the traditional
Turkevich/Frens’ approach, nanoparticle size, nanoparticle polydispersity, and the overall
reaction mechanism are determined by the solution pH set by [Na3Ctr].31
Unfortunately, as the
Na3Ctr/HAuCl4 ratio increases from 0 to 30 there is an increase in solution pH from 2.8 to 6.8
(Figure D3, Appendix D). Over this pH range, AuCl4- undergoes pH-dependent hydrolysis to
produce [AuClx(OH)4-x]- (x=0-4) complexes.
59 Due to the electron withdrawing capacity of the
hydroxyl ligand increased gold ion hydroxylation results in a decrease in standard reduction
potential (Figure D4, Appendix D).31, 60, 61
Past studies have shown that the final AuNP size can
be tuned by changing the solution pH due to this effect 31, 60
96
Addition of Na3Ctr without pH control causes the solution pH to increase above 6.2 during
the latter stages of AuNP synthesis. This change converts highly reactive AuCl3(OH)- into less
reactive complexes of AuClX(OH)4-X (x=0-2), and the reaction pathway consists of a single
nucleation-growth step.31, 61
Tight control of nanoparticle size is challenging under these
conditions because growth and nucleation occur simultaneously during the early stages of Na3Ctr
addition (i.e., when the pH < 6.2). To address this issue during seed preparation we set the
solution pH to a value of 6.4 by addition of 200 μL of 1 M NaOH to the reaction solution.
Figure 5-1A shows a typical TEM micrograph for seed nanoparticles synthesized using our
pH controlled synthetic protocol. The nanoparticles are highly monodisperse with a pseudo-
8 1 0 1 2 1 4 1 6 1 80
5
1 0
1 5
2 0
2 5
3 0
3 5
4 0
4 5
D iam ete r / n m
Fre
qu
en
cy
/a
.u.
w ith N aO H
w ith o u t N aO H
400 500 600 700 8000.0
0.2
0.4
0.6
0.8
1.0
1 10 1 00 1 0 000
5
1 0
1 5
2 0
2 5
In
ten
sit
y /
%
D iam eter / nm
S ize d is tribu tio n by in ten sity
Ab
so
rb
an
ce
W avelength / nm
w ith N aO H
w ithout N aO H
B
C D
A
Figure 5-1 - TEM micrographs of seed nanoparticles synthesized by (A) pH controlled method and (B)
w/o pH control; (C) TEM size distributions from both methods; (D) Normalized absorption spectra and
hydrodynamic size distribution by intensity (Inset) of two seed suspensions with (black lines) and w/o
pH controlled (red lines) procedures. Suspensions were diluted 3 and 9 for UV-vis and DLS
measurements, respectively.
97
spherical diameter of 13.9 ± 0.5 nm and an average aspect ratio (AR) of 1.06 ± 0.04. We also
calculated average particle diameters using Haiss’ equation (11) (with B1=3.00 and B2=2.20),53
based on the UV-vis spectra of the AuNP seeds. This particle diameter (13.6 ± 0.7 nm) closely
matched the average particle size obtained from TEM measurements (13.9 ± 0.5 nm). The size
distribution of 3.6% coincides with a highly reproducible DLS Z-average diameter and
polydispersity index (PDI), 17.7 ± 0.8 nm and 0.03 ± 0.01, respectively, for twelve replicate
batches. Particles synthesized without pH control (i.e., without adding NaOH) were also
characterized (as illustrated in Figure 5-1). For this synthesis, the pH value of 5.6 at the
beginning of reaction was set by the Na3Ctr/HAuCl4 ratio alone (Figure D3, Appendix D).
Compared with the pH controlled synthesis, an immediate color change (< 1 min) of the reaction
suspension was observed following Na3Ct injection, while the pH controlled reaction required 2-
3 min to see a similar color change, thus indicating faster nucleation and growth due to the
higher reactivity of the gold complexes at elevated pH (Figure D4, Appendix D). Although
Figure 5-1D shows the two syntheses have very similar LSPR λmax (517.9 nm for non pH
controlled particles, 518.5 nm for pH controlled particles), the hydrodynamic diameter and TEM
diameter of the nanoparticle increased from 15.2 nm to 17.7 nm and from 12.9 nm to 13.9 nm
respectively as the pH increased from 5.6 to 6.4. Consistent with the broader TEM size
distribution (Figure 5-1C) and absorption peak width at half maximum62
of the LSPR band
(Figure 5-1D), a larger PDI of 0.19 was obtained for the non-pH controlled particles along with
a 17% error between the particle size determined based upon the TEM measurements (12.9 nm
of ) and the size calculated using the Haiss equation (10.7 nm). As the initial AuIII
concentration
and the Na3Ct/HAuCl4 ratio were both fixed for the two seed synthesis approaches, this finding
98
is consistent with the previous observation that AuNP size and monodispersity of gold
nanocrystals are strongly dependent on the initial pH of the reaction medium.31
Room temperature seeded growth of AuNPs. Because of the rapid reaction kinetics at 100
oC it is necessary to keep Au
III and the reductant apart during seed-mediated growth
63 and the
order and speed of reagent addition strongly affect the final size and polydispersity of the
nanoparticles.62
To achieve improved nanoparticle homogeneity, we hypothesized that seeded
growth could be carried out at room temperature – and could simply be initiated following
addition of seed nanoparticles to premixed solutions of AuIII
and reductant (or alternatively the
introduction of AuIII
to a mixture of reductant and seeds). As illustrated herein, such an outcome
can be accomplished when the rate constant for surface mediated growth is significantly greater
than the rate constant for nucleation – a condition that occurs at room temperature. As shown in
Figure 5-2, by inoculating the growth medium with a controlled number of gold seeds, the
particles produced via this approach have sizes varying from 20-110 nm with the final size
dependent on the number of seeds and the total concentration of gold ions in the growth solution.
A majority of the NPs produced by this approach are quasi-spherical in shape, although
nanocrystal triangles and rods also form in low yield in the larger nanoparticle (>70 nm)
preparations (Supporting Information). Ignoring the presence of the non-spherical particles, the
average diameters and concentrations of the particles were determined and are tabulated in Table
5-1. For this calculation, we assumed that all of the particles exhibit spherical geometries.
However, as illustrated in Figure 5-2 this assumption becomes increasingly incorrect for the
larger nanomaterial sizes. We note that the similarity in particle size determined experimentally
and predicted using equation (3) suggests that nucleation of small nanoparticles does not occur,
99
thus indicating that the final concentration of AuNPs correlates well with the initial number of
AuNP seeds.
100
Table 5-1 - Sizes, concentrations, zeta-potentials, and optical properties of seeded AuNPs
AuNP
SPR
peak
(nm)
Concentration
(NPs/mL)a
Mean
potential
(mV)
Diameter of AuNP (nm)
Calculatedb
TEMc Z-average/PDI
(DLS)
A 525.9
5.5×1011
1.3×1011
5.4×1010
2.7×1010
1.6×1010
9.7×109
6.5×109
4.6×109
3.3×109
-40.5±1.2 22.7 24.0±6.1 25.9/0.193
B 533.9 -40.2±0.7 34.2 37.1±4.6 25.0/0.53
C 536.5 -38.7±1.1 45.7 46.0±4.6 31.2/0.502
D 537.2 -40.7±1.6 57.1 57.6±4.5 45.9/0.314
E 541.2 -42.7±0.5 68.6 69.6±11.8 61.2/0.239
F 551.9 -43.5±0.6 80.0 82.5±14.0 79.2/0.162
G 561.2 -44.4±1.5 91.4 92.4±11.4 89.7/0.148
H 569.9 -42.2±2.7 102.9 100.0±11.4 97.8/0.113
I 581.9 -46.6±1.4 114.3 111.0±8.3 105.8/0.114
aTheoretical concentration of seeded AuNPs based upon the seed concentration and assuming
that all gold salt precursors are reduced to gold atoms that condense onto the seed particle
surface; bParticle sizes as determined using Eq 3 for a seed concentration of 6.54×10
12 particles / mL.
cFor the particles with one dimension elongated, the sizes are overestimated by
[(AR)1/6
-1]100%. (where AR is the aspect ratio of the elongated particle).
101
As indicated in Table 5-1 and Figure D6A (Appendix D), we determined the hydrodynamic
diameter and size distribution of the AuNPs using DLS. The extreme sensitivity of the scattered
signal to changes in the radius (R) of the scattering objects (scattered intensity R6),
64 enables
DLS to detect the presence of even small numbers of aggregates in NP dispersions. The seeded
AuNPs in our work are not true spheres and should be described as ovoid with one dimension
elongated relative to the other. The effects of rotational diffusion result in the appearance of a
false peak in a size range of about 5-10 nm during DLS measurement for size distribution by
Figure 5-2 - TEM images of room temperature seed-mediated AuNPs of different sizes (aspect ratio):
A) 24.0±6.1 nm (AR: 1.15±0.17), B) 37.1±4.6 nm (AR: 1.15±0.11), C) 46.0±4.6 nm (AR: 1.34±0.14),
D) 57.6±4.5 nm (AR: 1.14±0.06), E) 69.6±11.8 nm (AR: 1.13±0.07), F) 82.5±14.0 nm (AR:
1.13±0.07), G) 92.4±11.4 nm (AR: 1.15±0.11), H) 100±11.4 nm (AR: 1.11±0.11), I) 111.0±8.3 nm
(AR: 1.11±0.09). Inset: histograms of diameters as determined by NIH ImageJ software.
102
intensity.65
This artifact causes the hydrodynamic size determined by DLS to be smaller than the
TEM determined core size, a result consistent with production of AuNPs by seed-mediated
growth at 100 oC.
66, 67
Gold nanoparticles display colors and LSPR bands in the visible spectral region that are
dependent upon NP size and shape.11, 68, 69
The origin of the LSPR band is the coherent excitation
of free conduction electrons due to polarization induced by the electric field of the incident light.
A change in the absorbance or wavelength of the LSPR band provides a measure of particle size,
shape, as well as aggregation state. UV−vis measurements were obtained to provide additional
characterization of the nanoparticle properties. In Figure D6B (Appendix D), we provide both
optical images and normalized UV-vis spectra for AuNPs of different sizes. For nanoparticle
diameters between 14 and 120 nm, the color exhibits a smooth transition from dark red to pink
and ultimately to yellowish brown. As expected,70
the LSPR wavelength is dependent on the
nanoparticle size, as evinced by the increase of the maximum absorbance wavelength (λmax) from
518 to 582 nm for nanoparticles of increasing size. This red shift is accompanied by the
broadening of the LSPR band in the long wavelength region. This broadening may be due to an
increase in polydispersity,71
particle agglomeration,31
or a combination of both processes.
Samples left at room temperature in the dark often agglomerated and precipitated, but could be
easily re-suspended by shaking or sonication. Such storage exhibited no effect on nanoparticle
stability.
103
Monitoring seed-mediated AuNP growth process. During AuNP synthesis, Ctr3-
is oxidized
to acetone dicarboxylate (ACDC2-
; eqn. 5), a ligand that complexes AuIII
, thus facilitating
nanoparticle growth. Following nanoparticle nucleation, ACDC2-
is thought to be rapidly
degraded to acetate at the synthesis temperature of 100 oC.
9
2 AuCl4-+3 Ctr
3- → 2 Au+3 ACDC
2-+3 CO2↑+8 Cl
-+3 H+ (5)
ACDC2− + 2H2O100℃→ acetone + 2CO2 ↑ +2OH
− (6)
Figure 5-3 - Seed mediated growth for AuNPs (C) with mixed solution of HAuCl4 (0.254 mM), Au seeds
(5.35×1010
particle/ml), and Na3Ctr (0.17 mM) at room temperature. TEM images of particles obtained at
different growth times.
104
Past studies suggest that ACDC2-
or its degradation products take part in additional redox
reactions when the Na3Ctr /HAuCl4 ratio is less than 1.5.62
Of particular relevance is a model
developed based upon the kinetics of the AuNP formation which suggests that acetone or other
carboxylate byproducts formed by the degradation of ACDC2-
(eqn. 6) reduce auric chloride and
lead to its complete conversion to Au0 (eqn. 7).
9, 39
(7)
Summing up equations 5-7 and correcting for the reaction stoichiometry provides the
following:
2AuCl4− + Ctr3− +2H2O
100℃→ 2Au + 3CH2O + 3CO2 ↑ +8Cl
− + 3H+ (8)
This model, however, does not consider the effects of temperature on ACDC2-
degradation.
At room temperature it is known that ACDC2-
undergoes slow oxidation in the presence of
oxygen:72
(9)
We speculate the following similar reaction occurs preferentially in the presence of AuIII
:
6 ACDC2-
+22 AuCl4-+24H2O
Room Temp.→
22Au+6CH2O+3HCOOH+21CO2+88Cl-+54H+
(10)
By summing up equations 5 and 10, the reaction stoichiometry in equation 11 indicates that
1 mol of citrate can reduce > 4 mol of HAuCl4.
6 Ctr3-
+26 AuCl4-+24 H2O
Room Temp.→
26Au+6CH2O+3HCOOH+27CO2+104 Cl-+60 H
+ (11)
We note that both Ctr3-
and ACDC2-
are carboxylates and that any byproducts of their
oxidation, reduction, or degradation are likely to contain carboxylate groups.73
Therefore, the
carboxylate moiety is a likely means of interaction agent with the AuNP surface regardless of the
exact species involved in AuNP capping.74, 75
4 AuCl4- + 6 H
2O+3 acetone
100 C¾ ®¾¾¾ 4 Au + 9 CH
2O+12 H+ +16 Cl-
2 ACDC2- +H2O + 5.5 O
2Room Temp.
¾ ®¾¾¾¾¾ 2 CH2O+HCOOH+7 CO
2+ 4 OH-
105
As noted previously, room temperature reaction conditions slow the AuNP synthesis
reaction, thus allowing for improved opportunities to characterize the seeded growth process. At
room temperature, the suspension color changed very slowly, but followed a similar sequence as
the traditional process at elevated temperature (i.e., from pale pink (seeds), to dark blue, to
purple). Figure 5-3 shows typical TEM images for different growth times for seed mediated
AuNPs prepared at a Na3Ctr/HAuCl4 ratio of 0.67 and a seed concentration of 5.35×1010
particles/mL (this corresponds to the ‘Type C’ AuNPs in Table 5-1). As shown in Figure D7
(Appendix D), the UV absorption of Na3Ctr decreases dramatically following AuIII
addition, thus
indicating its rapid coordination with AuIII
. In this synthesis, Na3Ctr facilitates coordination of
AuIII
ions around the AuNP seeds. This coordination involves fast ligand exchange between the
carboxylates and chlorine ions within the AuClX(OH)4-X complexes.37
Previous studies suggest that the mode of interaction between Na3Ct and AuNPs/Au ions is
likely through a bidentate bridging mode or via unidentate or chelate modes.39, 76-78
As shown in
Figure 5-3A, within 2 minutes of mixing the AuNP seeds with Na3Ctr and HAuCl4 we observed
formation of large (> 100 nm) weakly associated clusters that consist of large numbers of AuNP
seeds. These images are very similar to the large fluffy clusters observed by Chow and Zukoski
in the early stage of AuNP synthesis at 60 oC.
35 Some of these crystallites may have formed
following the drying of the suspension on the TEM grid. Nonetheless, this result suggests that
carboxylates bound to the seed surface and present in the growth medium enhance the
association between AuNP seeds and AuIII
ions (Scheme 1). After 30 minutes the clusters are no
longer observed and have broken apart due to the continued reaction between the carboxylates
and AuIII
and the suspension exhibits a light blue color. Figure 5-3B shows irregular gold
nanowires together with aggregates at this growth stage, a result similar to the observations by Ji
106
et al.31
and Pei et al.79
for nanoparticles produced using Frens’ method.8 After 1 hour, the gold
nanowires form fluffy spherical networks (diameter 100 nm; Figure 5-3C). In Figure 5-3C
(inset), some irregular gold nanowires remain isolated from the larger network. As the reaction
proceeds, however, the network continues to grow in size (Figure 5-3D). Similar trends in the
AuNP synthesis progress at elevated temperatures have been reported by previous researchers.35
After two hours, the fluffy network breaks apart into smaller segments (Figure 5-3E).
Ultimately, as the color of the reaction suspension changes color to purple-red, spherical
nanoparticles with diameter of 30-40 nm cleave off of the nanowires (Figure 5-3F). At the
conclusion of the reaction, evinced by the unchanging particle diameter (Figure 5-4B) and LSPR
peak (Figure 5-4C), the suspension attains a purple-red color and well-defined particles of 46
nm diameter are observed (Figure 5-2C).
Scheme 5-1 - Reactions among Au seeds, citrate and AuCl4
- after initial mixing.
Aliquots of the reaction suspensions were also extracted and monitored by DLS and UV-Vis
to further characterize the particle growth process depicted in Figure 5-3. Figure 5-4A illustrates
107
the intensity weighted hydrodynamic size distributions determined by DLS at different growth
stages. In addition to the peak for the seeded particles in the region of 10-100 nm, a small size
distribution peak was detected after 1 hour of growth. This peak can be explained as a result of
the formation of non-spherical particles with one dimension elongated relative to the other. The
effects of rotational diffusion result in the appearance of a false peak in a size range of about 5-
10 nm during DLS measurement.65
The presence of this peak is also consistent with the TEM
results in Figure 5-3 C-F that show that there is a small proportion of particles with sizes less
than 10 nm. The mean diameter of the major peak located between 10–100 nm increased
dramatically (Figure 5-4B) within an hour of Na3Ctr addition and then stabilized at 57 nm after
3 hours. The latter phenomenon agrees with the TEM result in Figure 5-3F, which shows that at
this point the reaction progress has neared completion of the “cleave” process. Interestingly,
there is no evidence in either Figure 5-4A or 5-4B of spherical networks with size in excess of
100 nm, which suggests that the large networks may have formed during TEM sample
preparation. Capillary drying forces are well known to result in enhanced nanoparticle
association following drop drying.80
The association between solution phase AuIII
and the AuNPs
is reflected in the absorption spectra in Figure 5-4C. There was a board absorption at
wavelengths > 600 nm that increased in magnitude as time increased from t=2 min to t=92 min.
This phase of the particle size evolution corresponds to Figure 5-3 A-D, during which the
AuNPs form fluffy networks. The broadening of the LSPR peak in the region > 600 nm (Figure
5-4C) and the increased absorbance at 700 nm (Figure 5-4C inset) corresponds to these fluffy
networks. After 92 minutes, a sharp red-shift in the LSPR peak was observed (Figure 5-4C),
which has been referred to as “turnover” in the literature81
. The “turnover” point at t=92 min
supports the structure/size change from Figure 5-3D to 5-3E, during which the fluffy networked
108
structure gave way to discrete AuNPs, which also corresponds to the decreased absorbance at
700 nm (Figure 5-4C inset).
Reaction supernatants separated by centrifugation at each reaction time were analyzed by
UV-vis spectroscopy and ICP-MS. As shown in Figure 5-5, the absorbance at 218 nm, which
corresponds to unreacted AuIII
,82
decreases rapidly after the initial mixing of the reagents,
stabilizes for approximately 30 minutes, and then decreases linearly with time. Compared to the
initial AuIII
peak intensity at 218 nm, 30% of AuIII
was reduced after the initial mixing of the
reagents. A total of 93% Au was detected by ICP-MS in the reaction supernatant, which may
1 10 100 1000
A
Diameter / nm
23 hr 53 min
11 hr 53 min
3 hr 4 min
2 hr 34 min
2 hr 2 min
1 hr 48 min
1 hr 32 min
1 hr 18 min
1 hr 3 min
44 min
33 min
2 min
Inte
nsi
ty /
% 0 5 10 15 20 2520
25
30
35
40
45
50
55
60 B
Mea
n d
iam
eter
of
pea
k 1
/ n
mTime / hour
400 500 600 700 800
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
1 h 32 min
1h 32 min
0 5 10 15 20 25
0.00
0.03
0.06
0.09
Ab
sorb
ance
at
70
0 n
m
Time / hour
C
Tim
e
Abso
rban
ce
Wavelength / nm
Figure 5-4 - (A) Size distribution by intensity, (B) mean diameter of peak 1 (located in the range of 10 –
100 nm in A) and (C) UV-vis absorption spectra obtained at different time stages of seed growth synthesis
of AuNPs.
109
include the intermediate reduced product of AuIII
or very small AuNPs. Such a result is
consistent with rapid coordination between the carboxylates and AuIII
and association of these
complexes with the Au seeds (i.e., the clusters of seeds and AuIII
shown in Figure 5-3A). The
AuIII
concentration was then stable for next 30 minutes. Such a result suggests that the initial
oxidation-reduction reaction only takes place in the clusters shown in Figure 5-3A and Scheme
1, which is consistent with the change from Figure 5-3A to 5-3B. After the initial 30 minutes of
reaction, the concentration of both AuIII
and total Au in the supernatant began to decrease
linearly and a total reaction time of 5 hours was observed. We used UV-vis spectroscopy to
verify that the AuNP growth reaction proceeded according to equation 11. A mixture of HCl and
NaCl with relative concentrations based upon the stoichiometry of equation 11 was prepared to
compare the UV absorption of supernatant of the reaction solution after 5 hours reaction. A
perfect match of the spectra shown in Figure D8 (Appendix D) provides evidence that the
stoichiometry of the room temperature seed mediated growth process is reasonably described by
equation 11. Moreover, no residual gold chloride ion was detected in the UV-vis spectrum of the
supernatant. As has been previously reported31
, residual gold ion can be detected in the UV-vis
spectra. The absence of this peak in the final UV-vis spectra suggests that there was no residual
gold ion. For this reason a 100% reaction yield was assumed, which was also verified by the
ICP-MS results in Figure 5-5. To the best of our knowledge this is the first time a reaction
stoichiometry has been developed for room-temperature seed-mediated AuNP synthesis.
110
Evaluation of room temperature seeded AuNPs. The as-prepared AuNPs exhibit
exceptional colloidal stability and can be stored at room temperature over several months in spite
of their slow agglomeration. The nanoparticles could be easily re-suspended by shaking or
sonication. This result suggests these particles can be favorably employed for SERS applications.
Figure 5-6 gives the comparison of surface Raman enhancement of MGITC adsorbed on seed
mediated 46 nm AuNPs produced at room temperature and those produced at 100 oC (Figure
D9, Appendix D). Importantly, the AuNPs prepared at room temperature exhibit a 2 greater
Figure 5-5 – Time-dependent AuIII
and Au level in supernatant by UV-vis (squares) and ICP-MS
(triangles). Inset: corresponding UV absorption spectra. Dash black line is the spectrum of the initial
AuIII solution. Prior to the UV-vis measurement, all AuNP suspensions were diluted 2 with deionized
water.
0 5 10 15 20 25
0
20
40
60
80
100
200 250 300 350 400 450 500
0.0
0.4
0.8
1.2
1.6
2.0
Tim
e
Abso
rban
ce
Wavelength / nm
Au i
n s
uper
nat
ant
(%)
Time (hour)
111
Raman enhancement than AuNPs prepared at 100 oC. We attribute this enhancement to the
greater surface roughness of the room temperature AuNPs.83
The particles with edges, corners or branches (e.g., nanorods, nanostars) were stable at low
temperatures, but are likely to transform into more thermodynamically stable shapes (spheres) if
sufficient thermal energy were provided for atomic reorganization. The particles prepared at
room temperature had more edges and corners than 100 °C prepared particles, as shown by TEM
images (Figure D9, Appendix D). Due to the same concentration and volume of AuNPs, the
surface area of the resulting particles at room temperature will larger than those synthesized at
100°C, which explains increased surface roughness compared to AuNPs prepared at 100°C.
Comparative LCA. The cumulative energy demand (CED) of the AuNP synthesis methods
from the LCA models are presented in Table 5-2. The results show that despite the longer
400 800 1200 1600 2000
46 nm MGITC-AuNP (100 oC)
46 nm MGITC-AuNP (RT)
Inte
nsi
ty /
a.u
.
Raman shift / cm-1
Figure 5-6 - SERS spectra of MGITC (20 nM) adsorbed on room temperature and 100 oC seed
mediated AuNPs under 633 nm excitation. MGITC-AuNPs were prepared by quickly adding 1.5 L of
14 M MGITC solution to 1 mL AuNP suspension (5.4×1010
particle/mL).
112
reaction time, AuNP synthesis at room temperature has lower CED than synthesis under boiling
conditions. The trend of the other impacts across different impact categories matches that of the
CED (Figure D10, Appendix D). This result is expected as CED has been shown to correlate
well to other environmental impact methods (e.g., EcoIndicator, EcoScarcity, etc.).84
This
observation is understandable because the use of fossil fuels (included in CED) is a dominant
driver of many environmental impacts.85
Uncertainty analysis shows that the differences in the
environmental impacts for AuNP synthesis at room
temperature and under boiling conditions are statistically
significant (Figure D11, Appendix D). Although
laboratory-scale room temperature synthesis does seem to
reduce the energy footprint of AuNP synthesis (compared
to the conventional approach at higher temperatures),
further studies on scale-up scenarios are recommended,
since the environmental footprints are likely to be
influenced by yield, energy efficiencies and the available
energy sources and fuel-mixes.86, 87
Conventional scale-up
of boilers and generators has been shown to follow a
power law relationship.88, 89
However, similar
relationships for scaling up have not been established for
nanoparticle synthesis. Longer reaction times in pilot-
scale and commercial-scale setups will involve additional
Table 5-2 - Cumulative energy demand
(CED) for AuNP synthesis at room
temperature vs. boiling conditions. The
CEDs for AuNP syntheses at room
temperature and under boiling conditions
are 1.25 MJ and 1.54 MJ respectively.
113
energy demands (e.g., lighting, heat ventilation, air-conditioning etc.) which should also be
considered in scale up scenarios. The role of regional variability in the energy and water
footprints should also be factored into future decisions about nanomaterials industry siting and
resource allocation.
CONCLUSIONS
A simple room temperature seed mediated preparation route for AuNPs has been
demonstrated. Tunability of the AuNP diameter was achieved by simply varying the number
concentration of seeds under mild environmental conditions. Such a result shows a promising
colorimetric assay using the size-dependent optical property. The continuous surface plasmon
oscillations associated with this broad spectral feature gives them broad selection in the future
SERS applications. Our reported AuNP synthesis approach helps decrease the rate of AuNP
growth due to the milder (room temperature) conditions, thus providing increased opportunities
to study a very complicated reaction mechanism. Moreover, this method shows significant
reductions in the cradle-to-gate life cycle impacts compared to the previously reported methods
that employed boiling conditions.
ACKNOWLEDGEMENTS
This work was supported by grants from the Virginia Tech Graduate School (Sustainable
Nanotechnology Interdisciplinary Graduate Education Program), the Virginia Tech Institute of
Critical Technology and Applied Science (ICTAS), and NSF Award CBET-1133746.
114
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Chapter 6
Summary
Novel approaches for nanomaterial synthesis that employ renewable, bio-based reagents
may intuitively seem green. However, these methods must be analyzed from a life cycle
perspective to identify hidden environmental costs. LCA of green synthesis of AuNPs showed
that the main driver of environmental burdens associated with AuNP synthesis is the large
embodied energy of gold. Moreover, reaction yield, which is seldom reported in the literature for
green synthesis of nanomaterials, greatly influenced the life cycle impacts of the overall
synthesis. The large embodied energy of gold hinted at the potential for reducing the life cycle
impacts of AuNP synthesis through recycling. To achieve this objective, host-guest inclusion
complex formation facilitated by -cyclodextrin (recently reported by Liu et al., (2013)) was
employed to successfully recover gold from nanomaterial waste. A major advantage offered by
this approach for selective gold recovery over conventional approaches is that the recovery does
not involve the use of toxic cyanide or mercury. LCA modeling showed that recycling gold from
nanomaterial waste can substantially reduce the life cycle environmental impact of AuNP
synthesis. With regard to citrate-reduced AuNPs, conducting the synthesis at room temperature
instead of boiling reduced the energy footprint. Moreover, the slow growth of AuNPs at room
temperature provided new opportunities for tuning and controlling AuNP size and morphology.
The research presented in this dissertation is an effort to combine laboratory techniques with
life cycle modeling to gain new insights into the sustainability of nanotechnology. However,
both aspects – laboratory techniques and LCA modeling - have limitations that pose challenges
for assessing the life cycle impacts of nanotechnologies. A major challenge in conducting LCAs
of nanomaterials is the difficulty in defining appropriate functional units for comparative studies,
122
because nanomaterials and their synthesis methods are often tailored for unique functionalities
that cannot be compared readily. In Chapter 2 and 5, the LCA models for AuNP synthesis
excluded the use phase, and were limited to cradle-to-gate analyses. The use phase was also
excluded in the LCA studies on AuNP recycling (Chapter 3). This limitation was due to the lack
of a single, well-established large-scale use of AuNP, in which the enhanced functionality
enabled by AuNPs could be compared with technologies that did not employ AuNPs. Therefore
mass was used as the functional unit in the LCA studies reported in Chapter 2, 3 and 5. Indeed,
several researchers have conducted cradle-to-gate LCAs for nanotechnologies using mass as a
functional unit1-10
. Mass has also been used as a functional unit even for products from mature
industries (e.g., margarine and butter11
) in comparative LCAs. As a baseline, mass does not
capture the functionality associated with the use of nanomaterials. Nonetheless, by using mass as
a functional unit, a screening-level, cradle-to-gate LCA of a novel product (e.g., AuNPs) with
wide-ranging applications downstream can be a valuable initial step towards more
comprehensive LCAs in the future. In addition to defining functional units, compiling the
inventories for LCAs on nanomaterials is another challenge. Information about nanomaterial
synthesis methods is often proprietary, which makes quantification of the material and energy
flows involved in nanomaterial production difficult.12
Therefore substantial uncertainties exist in
the production and release estimates for nanomaterials. While such uncertainties exist due to data
gaps, another factor that introduces uncertainty in LCAs is the natural process-to-process and
product-to-product variability in the inventory, as well as due to effects of scale-up, improved
process efficiencies and the maturing of technologies.
Laboratory and field studies are required to determine the fate and transport, as well as
toxicity of nanomaterials in order to inform LCA studies. This information is necessary for
123
developing nano-specific characterization factors to be used in life cycle impact assessment.
However, given the unique properties of nanomaterials, standardized fate and transport studies
and toxicological assessments for nanomaterials have not been developed. It is important to note
that the LCA studies presented in this dissertation do not account for nano-specific toxicity of
gold, because that information is currently not available in impact assessment methods.
However, the lack of nano-specific toxicity information in impact assessment methods is not a
limitation of LCA, which was originally developed as a framework for studying mature
technologies. As nanotechnology matures and the data about the toxicity of different
nanomaterials becomes more robust through laboratory and field experiments, nano-specific
characterization factors can be developed and integrated in life cycle impact assessment.
Life cycle thinking needs to be a part of nanotechnology, and research efforts should be
focused on developing nano-specific characterization factors and impact assessment methods.
However, it is not enough to tailor nanotechnology research findings to fit into the traditional
LCA framework. Traditional LCAs are retrospective. In addition to streamlining nanotechnology
research findings to fit into environmental systems analysis framework, a key research challenge
is the development of new life cycle modeling and decision analysis approaches that are
adaptive, nimble and anticipatory13
in order to meet the challenges of emerging
nanotechnologies.
Lessons from costly environmental mistakes made in the past urge us to consider the
unforeseen implications of promising new technologies. Innovations in regulations and policy
measures, however, have been outstripped by technological progress. Given the data gaps and
uncertainties related to nanotechnology, it may be tempting to rely on intuition when making
decisions or policies. However, intuitions about what is ‘green’ and sustainability may prove to
124
be wrong. The research presented in this dissertation shows that life cycle thinking to be an
effective inoculation against intuitive, but sometimes faulty notions about sustainability.
Regulations and policy measures informed by LCAs are therefore required for the continued
growth of nanotechnology and its stewardship along sustainable paths.
125
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2011, 45, (7), 2562-2569.
13. Wender, B.; Foley, R. W.; Prado-Lopez, V.; Eisenberg, D. A.; Ravikumar, D.; Hottle, T. A.;
Sadowski, J.; Flanagan, W. P.; Fisher, A.; Laurin, L.; Seager, T.; Bates, M. E.; Fraser, M. P.; Linkov, I.;
Guston, D. H., Illustrating Anticipatory Life Cycle Assessment for Emerging Photovoltaic Technologies.
Environmental Science & Technology 2014.
127
Appendix A
Supplementary materials for Chapter 2
Life cycle assessment of “green” nanoparticle synthesis methods
Paramjeet Pati1,2,3
, Sean McGinnis2,4
, and Peter J. Vikesland1,2,3
*
1Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, Virginia
2Virginia Tech Institute of Critical Technology and Applied Science (ICTAS) Sustainable
Nanotechnology Center (VTSuN), Blacksburg, Virginia
3Center for the Environmental Implications of Nanotechnology (CEINT), Duke University, Durham,
North Carolina
4Department of Materials Science and Engineering and Virginia Tech Green Engineering Program,
Virginia Tech, Blacksburg, Virginia
*Corresponding author. Phone: (540) 231-3568, Email: [email protected]
Environmental Engineering Science 31.7 (2014): 410-420
DOI: 10.1089/ees.2013.0444.
Reprinted (adapted) with permission from Mary Ann Liebert, Inc.
128
Table A 1 - Environmental impacts across all impact categories for 1 mg AuNP synthesized using borohydride, citrate, hydrazine, soybean seeds and
sugarbeet pulp. (The errors show 95% interval. The source of the error in each case is the combined effect of the uncertainty due to energy use and gold
salt (chloroauric acid) model.)
Impact category Unit borohydride citrate Hydrazine soybean seed sugarbeet pulp
Agricultural land
occupation m2a 5.89 × 10-4 ± 3.10 × 10-4 7.21 × 10-4 ± 3.40 × 10-5 8.07 × 10-4 ± 3.86 × 10-4 3.01 × 10-3 ± 8.90 × 10-4 1.46 × 10-3 ± 7.04 × 10-4
Climate change kg CO2 eq 2.88 × 10-2 ± 5.4 × 10-3 3.14 × 10-2 ± 5.35 × 10-3 3.45 × 10-2 ± 6.30 × 10-3 3.64 × 10-2 ± 5.95 × 10-3 4.75 × 10-2 ± 7.15 × 10-3
Fossil depletion kg oil eq 7.99 × 10-3 ± 2.36 × 10-3 8.78 × 10-3 ± 2.27 × 10-3 9.68 × 10-3 ± 2.86 × 10-3 1.02 × 10-2 ± 2.56 × 10-3 1.36 × 10-2 ± 3.20 × 10-3
Freshwater
ecotoxicity kg 1,4-DB eq 1.38 × 10-4 ± 1.10 × 10-4 1.38 × 10-4 ± 1.07 × 10-4 1.49 × 10-4 ± 1.18 × 10-4 1.39 × 10-4 ± 1.03 × 10-4 1.37 × 10-4 ± 1.09 × 10-4
Freshwater
eutrophication kg P eq 1.15 × 10-3 ± 1.38 × 10-3 1.23 × 10-3 ± 1.40 × 10-3 1.33 × 10-3 ± 1.64 × 10-3 1.20 × 10-3 ± 1.37 × 10-3 1.19 × 10-3 ± 6.73 × 10-3
Human toxicity kg 1,4-DB eq 1.13 × 10-2 ± 6.99 × 10-3 1.16 × 10-2 ± 6.82 × 10-3 1.26 × 10-2 ± 8.26 × 10-3 1.15 × 10-2 ± 7.01 × 10-3 1.20 × 10-2 ± 1.45 × 10-3
Ionizing
radiation kBq U-235 eq 5.25 × 10-3 ± 7.57 × 10-3 7.86 × 10-3 ± 1.25 × 10-2 8.82 × 10-3 ± 1.50 × 10-2 1.16 × 10-2 ± 1.85 × 10-2 2.16 × 10-2 ± 3.69 × 10-2
Marine
ecotoxicity kg 1,4-DB eq 1.75 × 10-4 ± 1.07 × 10-4 1.75 × 10-4 ± 9.90 × 10-5 1.88 × 10-4 ± 1.11 × 10-4 1.77 × 10-4 ± 1.02 × 10-4 1.79 × 10-4 ± 1.04 × 10-4
Marine
eutrophication kg N eq 6.99 × 10-5 ± 4.49 × 10-5 7.10 × 10-5 ± 4.51 × 10-5 7.65 × 10-5 ± 4.54 × 10-5 8.11 × 10-5 ± 4.89 × 10-5 7.23 × 10-5 ± 4.60 × 10-5
Metal depletion kg Fe eq 1.0 × 10-1 ± 2.02 × 10-2 9.99 × 10-2 ± 2.10 × 10-2 1.10 × 10-1 ± 2.59 × 10-2 9.99 × 10-2 ± 2.09 × 10-2 1.00 × 10-1 ± 2.06 × 10-2
Natural land
transformation m2 1.36 × 10-5 ± 8.65× 10-6 1.38 × 10-5 ± 8.70 × 10-6 1.52 × 10-5 ± 1.04 × 10-5 1.40 × 10-5 ± 9.11 × 10-6 1.46 × 10-5 ± 1.07 × 10-5
Ozone depletion kg CFC-11 eq 2.97 × 10-9 ± 1.48 × 10-9 3.15 × 10-9 ± 1.42 × 10-9 3.37 × 10-9 ± 1.55 × 10-9 3.57 × 10-9 ± 1.48 × 10-9 4.51 × 10-9 ± 1.80 × 10-9
Particulate
matter formation kg PM10 eq 1.01 × 10-4 ± 3.13 × 10-5 1.06 × 10-4 ± 3.25 × 10-5 1.16 × 10-4 ± 3.65 × 10-5 1.14 × 10-4 ± 3.16 × 10-5 1.33 × 10-4 ± 4.07 × 10-5
Photochemical
oxidant
formation
kg NMVOC 3.07 × 10-4 ± 1.17 × 10-4 3.11 × 10-4 ± 1.16 × 10-4 3.40 × 10-4 ± 1.35 × 10-4 3.21 × 10-4 ± 1.12 × 10-4 3.42 × 10-4 ± 1.20 × 10-4
Terrestrial
acidification kg SO2 eq 2.73 × 10-4 ± 7.85 × 10-5 2.92 × 10-4 ± 8.35 × 10-5 3.22 × 10-4 ± 9.65 × 10-5 3.29 × 10-4 ± 9.45 × 10-5 4.13 × 10-4 ± 1.48 × 10-4
Terrestrial
ecotoxicity kg 1,4-DB eq 9.09 × 10-6 ± 7.20× 10-6 9.25 × 10-6 ± 7.30 × 10-6 1.01 × 10-5 ± 8.29 × 10-6 9.15 × 10-6 ± 6.67 × 10-6 9.51 × 10-6 ± 7.19 × 10-6
Urban land
occupation m2a 3.26 × 10-3 ± 1.51 × 10-3 3.27 × 10-3 ± 1.51 × 10-3 3.60 × 10-3 ± 1.77 × 10-3 3.30 × 10-3 ± 1.56 × 10-3 3.35 × 10-3 ± 1.52 × 10-3
Water depletion m3 6.66 × 10-2 ± 1.35 × 10-2 1.07 × 10-1 ± 1.73 × 10-2 1.24 × 10-1 ± 2.10 × 10-2 1.76 × 10-1 ± 3.25 × 10-2 3.46 × 10-1 ± 7.40 × 10-2
129
Table A 2 - AuNP morphology, reaction conditions, CEDs for the different synthesis methods (assuming 100% reaction yield).
Source of
reducing agent
AuNP morphology and
size distribution
Reaction
Time
Temp
(° C)
Yield
(%)
% Contribution to CED
Gold
salt
Reducing
agent Energy
Cleaning
solvent
DI
water
Tap
water
Sodium
borohydride1
Particle size information was not reported < 5 min RT NR 83.6% 0.29% 0.80% 13.3% 1.98% 0.32%
Citrate2 Near spherical particles, 13 ± 5 nm. 15 min 100° C,
15 min
> 99.9% 72.2% 0.04% 14.68% 11.5% 1.64% 0.03%
Grape pomace3 Nearly spherical in (a) 10 -30 nm and (c) 5-10 nm. Anisotropic aggregates in (b) 40 –
50 nm. Microwaved for 60s (Power = 50 W)
3–48 h - 80% 86.9% - 0.52% 11% 1.57% 0.03%
Hydrazine4 Multi-branched nanoparticles with sizes between 20 – 130 nm 40 min RT NR 69.5% <0.01% 17.70% 11% 1.63% 0.03%
Cypress leaf
extract5
Nearly-spherical particles and agglomerates. Standard deviations not provided. Mean
diameter increased from 5 nm to 94 nm as extract concentration increased.
10 min RT 94% 27.9% - 67.29% 4.16% 0.61% 0.01%
C. camphora leaf
extract6
Near spherical, with some large nanotriangle aggregates.
15 to 25 nm with mean dia 23.4 nm for 0.5 g biomass, 21.5 nm for 1 g biomass
1 hour 30° C NR 79.5% - 6.09% 12.6% 1.81% 0.03%
Vitamin B2 7 Spheres, rods and nanowires. Controlled morphology by varying solvent density. 5–12
nm size range (8.1± 0.1 nm) in ethylene glycol. 6–16 nm size range(11.54 ± 0.1 nm)
in acetic acid,
30 min RT NR 78.3% - 7.51% 12.4% 1.78% 0.03$
Cinnamon8 AuNPs appear near spherical with some anisotropy. Reported dia 13 ± 5 nm The sizes
and morphologies are difficult to interpret from the TEM image provided.
30 min 25° C NR 71.1% - 15.9% 11.3% 1.61% 0.03%
C.album leaf
extract9
Near spherical shapes.
10nm-30nm for 1mM HAuCl4, 50-100 nm for 5 mM HAuCl4
15 min –
2h
RT NR 52.2% - 34.78% 8.76% 1.26% 0.02%
Soybean seed10 Spherical nanoparticles, 15 ± 4 nm in dia 4 h RT NR 58.7% 0.58% 30% 9.31% 1.33% 0.02%
Mushroom11 Anisotropic AuNPs with dodecahedral triangular, hexagonal and near-spherical 20 -
150 nm AuNPs were more spherical as extract concentration was increased. No
standard deviations/ size ranges provided.
2.5 h,
RT
NR
56% - 33.8% 8.88% 1.29% 0.02%
Ginseng12* Mostly spherical nanoparticles ranging from ranging from 2 to 40 nm. Mean dia 16.2 ±
3 nm
3 h RT NR 62% - 26.7% 9.84% 1.41% 0.02%
D-Glucose13 Discrete, near-spherical AuNPs with narrow size distribution, 5.6 nm sd = 1.37, 6.7 nm
sd = 1.24, 8.8nm sd = 1.39 nm
~60
min**
RT NR 46.7% - 44.8% 7.41% 1.06% 0.02%
Sugarbeet pulp14 Nanowires of 10 – 50 nm diameter, depending upon pH 5 h RT NR 40.2% <0.01% 52.4% 6.38% 0.94% 0.02%
Soybean seed
extract10
Spherical nanoparticles, 15 ± 4 nm in dia 70 min 95° C for
10 min
NR 30.9% <0.01% 63.60% 4.9% 0.7% 0.01%
Coriander leaf
extract15
Spherical, triangle, truncated triangles and decahedral morphologies. 6.75 nm to 57.91
nm with an average size of 20.65±7.09 nm
12 h
RT NR 16.2% - 80.76% 2.58% 0.37% <0.01
%
Glossary shown below Table A 3
130
Table A 3 - AuNP reaction conditions, Freshwater Ecotoxicity and Agricultural Land Occupation for the different synthesis methods.
Source of
reducing agent
Reaction
Time
Temp
(° C) Yield
(%)
% Contribution to Freshwater Ecotoxicity % Contributions to Agricultural Land Occupation
Gold
salt
Reducing
agent Energy
Cleaning
solvent
DI
water
Tap
water
Gold
salt
Reducing
agent Energy
Cleaning
solvent
DI
water
Tap
water
Sodium
borohydride1
< 5 min RT NR 98.5% <0.01% <0.01% 0.57% 0.88% 0.04% 76.3% 0.26% 1.1% 18.4% 3.81% 0.09%
Citrate2 15 min 100° C,
15 min
> 99.9% 98.5% 0.01% 0.07% 0.56% 0.84% 0.04% 62.4% 0.49% 19.1% 15% 2.99% 0.08%
Grape pomace3 3–48 h - 80% 98.8% - <0.01% 0.45% 0.67% 0.03% 80.6% - 0.73% 15.5% 3.07% 0.08%
Hydrazine4 40 min RT NR 98.3% 0.13% 0.09% 0.56% 0.87% 0.04% 59.3% <0.01% 22.8% 14.2% 2.92% 0.07%
Cypress leaf
extract5
10 min RT 94% 97.7% - 0.89% 0.53% 0.80% 0.03% 20.4% - 74% 4.61% 0.93% 0.02%
C. camphora leaf
extract6
1 hour 30° C NR 98.5% - 0.03% 0.56% 0.84% 0.04% 71.2% - 8.22% 17.1% 3.41% 0.09%
Vitamin B2 7 30 min RT NR 98.5% - 0.04% 0.56% 0.84% 0.04% 69.7% - 10.1% 16.8% 3.34% 0.09%
Cinnamon8 30 min 25° C NR 98.5% - 0.08% 0.56% 0.84% 0.04% 61.5% - 20.7% 14.8% 2.93% 0.08%
C.album leaf
extract9
15 min –
2h
RT NR 98.3% - 0.23% 0.56% 0.84% 0.04% 44.7% - 42.4% 10.8% 2.14% 0.06%
Soybean seed10 4 h RT NR 98.3% 0.08% 0.19% 0.56% 0.84% 0.04% 15% 69% 11.6% 3.62% 0.72% 0.02%
Mushroom11 2.5 h,
RT
NR
98.3% - 0.23% 0.56% 0.85% 0.04% 45.4% - 41.4% 10.9% 2.21% 0.06%
Ginseng12* 3 h RT NR 98.4% - 0.16% 0.56% 0.84% 0.04% 51.6% - 33.4% 12.4% 2.46% 0.06%
D-Glucose13 ~60
min**
RT NR 98.2% - 0.34% 0.56% 0.84% 0.04% 36.6% - 52.8% 8.8% 1.74% 0.05%
Sugarbeet pulp14 5 h RT NR 98.1% <0.01% 0.48% 0.561% 0.86% 0.04% 30.7% <0.01% 60.3% 7.4% 1.51% 0.04%
Soybean seed
extract10
70 min 95° C for
10 min
NR 97.8 <0.01% 0.76% 0.56% 0.84% 0.04% 22.6% 0.83% 70%
5.44% 1.08% 0.03%
Coriander leaf
extract15
12 h
RT NR 96.8% - 1.82% 0.55% 0.83% 0.03% 11.4% - 85.3% 2.74% 0.55% 0.01%
NR – Not Reported (Assumed to be 100%), RT – Room temperature.
* Using ICP-MS, the authors reported residual gold content in the pellet obtained after centrifugation. Reaction yield was not reported.
** Actual duration for stirring was not reported. These values were estimated based on the description and data reported in the literature. References: 1 Lows and Bansal (2010), 2- Actual
measurements. 3, Baruwati and Varma (2009), 4 – Jeong et al. 2009, 5. Noruzi et al. 2012, 6. Huang et al. 2007, 7. Nadagouda and Varma (2006), 8. Chanda et al. (2009), 9. Dwivedi and
Gopal (2010), 10. Shukla et al. (2008), 11. Philip (2009), 12. Leonard et al. (2011), 13. Raveendran et al. (2006), 14 Castro et al. (2011). 15. Narayan and Sakthivel (2008)
131
COMPARATIVE LCA OF GREEN AND CONVENTIONAL SYNTHESIS METHODS
FOR AuNPs
For eleven out of the sixteen methods shown in Table A 2, greater than 60% of the CED can
be attributed to the gold salt used for synthesizing AuNPs. We note that although the energy cost
embedded in precious metals (e.g., gold) cannot be mitigated by green chemistry approaches, the
overall CED can be reduced by choosing the appropriate synthesis method. As shown in Tables
A2 and A3, when the green synthesis methods involve energy intensive processes (e.g.,
sonication; (“ginseng” - 1 and long reaction times (“coriander” -
2, the energy used during the
reaction (i.e., electricity) becomes increasingly important compared to the embodied energy in
the gold salt.
In all sixteen methods, greater than 96% of the freshwater ecotoxicity is due to gold salt (Table A 3).
Even for the methods that use toxic chemicals such as hydrazine and sodium borohydride, the
contributions of these chemicals to freshwater ecotoxicity were less than 0.15%. The impacts on
agricultural land occupation were an order of magnitude higher for soybean and sugarbeet pulp compared
to those from sodium borohydride. In the case of sugarbeet pulp (an agricultural waste), the energy
requirement for stirring accounted for over 60% of the agricultural land occupation, while the
contribution from sugarbeet pulp itself was negligible. In contrast, for the synthesis method using soybean
seed as reductant, the energy for stirring accounted to less than 12% of the agricultural land occupation
potential, while soybean seed itself accounted for 69% (Table A 2 and A 3). These results show the
substantial impact of upstream agricultural processes in the case of plant-derived chemicals.
132
Figure A 1 - The effect of different gold sources on the cumulative energy demand for citrate-reduced
AuNPs. (RoW: Rest of the world. RoW-a: Rest of the world (precious metals from electronic scrap.)
Error bars represent 95% confidence intervals for the combined uncertainties in the chloroauric acid and
citric acid models, energy use and uncertainties in the EcoInvent unit processes.
133
AuNP SYNTHESIS USING SPENT COFFEE AND BANANA PEEL EXTRACT
To investigate the quality (heterodispersity, colloidal stability) of AuNPs using plant-
derived chemicals, we developed synthesis protocols that used coffee ground (reductant) and
banana peel extract (stabilizer). AuNPs were prepared using spent coffee grounds as reductant
and aqueous banana peel extract as stabilizer. 5 g of spent coffee grounds and 20 g of scrapings
from banana peel were extracted using 100 mL and 200 mL (respectively) of deionized water at
room temperature for 30 minutes under constant stirring. The stirring was then stopped and the
heavier fractions were allowed to settle for 30 minutes. The lighter fractions of the extracts were
then decanted and filtered through 0.22 μm polyethersulfone (PES) filter (Millipore, Catalog #
SCGPT01RE) and stored at 4° C. 4 mL of the spent coffee grounds extract was added to a
reaction mixture containing 10 mL of 1 mM gold chloride trihydrate and 2.5 mL of the extract of
scrapings from banana peel. The synthesis reactions were conducted at 22° C, 40° C, 60° C and
80° C.
AuNPs were also prepared using tea as reductant and stabilizer as per the methods reported
by3. AuNP samples were analyzed by transmission electron microscopy (JEOL 2100 and Philips
EM420), Figure A2 shows the heterodispersity in AuNPs prepared using “green” synthesis
Figure A 2 - Heterodispersity in AuNP synthesis using plant-derived chemicals. A) and B) AuNPs
prepared using tea C) AuNPs prepared using coffee and banana peel extract at 80° C.
134
methods. Figure S2 A) and B) AuNPs prepared using tea C) AuNPs prepared using coffee and
banana peel extract at 80° C.
REFERENCES
1. Leonard, K.; Ahmmad, B.; Okamura, H.; Kurawaki, J., In situ green synthesis of biocompatible
ginseng capped gold nanoparticles with remarkable stability. Colloids and surfaces. B, Biointerfaces
2011, 82, (2), 391-6.
2. Narayanan, K. B.; Sakthivel, N., Coriander leaf mediated biosynthesis of gold nanoparticles.
Materials Letters 2008, 62, (30), 4588-4590.
3. Nune, S. K.; Chanda, N.; Shukla, R.; Katti, K.; Kulkarni, R. R.; Thilakavathi, S.; Mekapothula,
S.; Kannan, R.; Katti, K. V., Green Nanotechnology from Tea: Phytochemicals in Tea as Building Blocks
for Production of Biocompatible Gold Nanoparticles. J Mater Chem 2009, 19, (19), 2912-2920.
135
Appendix B
Supplementary materials for Chapter 3
Waste Not Want Not: Life Cycle Implications of Gold Recovery and
Recycling from Nanowaste
Figure B 1 - Powder X-ray diffraction of recovered gold. The highlighted peaks correspond to gold peaks.
The unidentified peaks are presumably due to impurities. XRD measurements were performed on a Rigaku
MiniFlex II instrument (Rigaku Americas, The Woodlands, TX, USA).
136
Figure B 2 - UV-vis spectra of recovered gold chloride and chloroauric acid standard. All measurements
were using a Cary 5000 UV-Vis-NIR spectrophotometer (Agilent, Santa Clara, CA). All samples were
scanned in quartz cuvettes (Starna, model# 1-Q-10) with 10 mm path length.
137
Figure B 3 - Crystal structure information from SAED measurements confirms that the recovered
precipitate is gold. TEM image shows highly aggregated citrate-reduced AuNPs produced by this
approach. The existence of ‘throats’ between individual AuNPs provides evidence of AuNP coalescence.
All TEM and SAED measurements were performed on a JEOL 2100 (JEOL, Peabody, MA, USA)
138
Table B 1 - Life cycle inventories for custom defined chemicals AuNP synthesis and recovery steps.
[Custom defined] Chloroauric acid (1 mg)
Gold {US}| production | Alloc Def, S 0.72 mg
Hydrochloric acid, without water, in 30% solution state {RER}| hydrochloric
acid production, from the reaction of hydrogen with chlorine | Alloc Def, S 0.13 mg
Chlorine, gaseous {RER}| sodium chloride electrolysis | Alloc Def, S 0.39 mg
[Custom defined] Trisodium citrate (1 mg)
Citric acid {GLO}| market for | Alloc Def, S 0.51 mg
Soda ash, light, crystalline, heptahydrate {GLO}| market for | Alloc Def, S 0.66 mg
[Custom defined] Hydrobromic acid (1 mg)
Phosphorus, white, liquid {GLO}| market for | Alloc Def, S 0.13 mg
Bromine {GLO}| market for | Alloc Def, S 0.99 mg
Water, deionised, from tap water, at user {GLO}| market for | Alloc Def, S 0.22 mg
[Custom defined] α-cyclodextrin (1 mg)
Potato starch {GLO}| market for | Alloc Def, S 1.67 mg
Water, deionised, from tap water, at user {GLO}| market for | Alloc Def, S 16.67 mg
[Stirring] Electricity, medium voltage {NPCC, US only}| market for | Alloc
Def, S 0.02 MJ
[Heating] Electricity, medium voltage {NPCC, US only}| market for | Alloc
Def, S 0.18 MJ
Table B 2 - Life cycle inventories for AuNP synthesis steps. Citrate-reduced gold nanoparticles (1 mg)
[Custom defined] Chloroauric acid 1.73 mg
[Custom defined] Trisodium citrate 5.08 mg
Water, deionised, from tap water, at user {CH}| production | Alloc Def, S 505.08 g
Tap water {CH}| market for | Alloc Def, S 30.00 g
Cleaning solvents
Hydrochloric acid, without water, in 30% solution state {RER}| hydrochloric
acid production, from the reaction of hydrogen with chlorine | Alloc Def, S 1.81 mg
Nitric acid, without water, in 50% solution state {RER}| nitric acid production,
product in 50% solution state | Alloc Def, S 0.72 mg
[Stirring] Electricity, medium voltage {NPCC, US only}| market for | Alloc
Def, S 0.01 MJ
[Heating] Electricity, medium voltage {NPCC, US only}| market for | Alloc
Def, S 0.08 MJ
139
Table B 3 - Life cycle inventories for AuNP recovery steps to treat 1 mg of gold nanowaste
AuNP precipitation using NaCl
Sodium chloride, powder {RER}| production | Alloc Def, S 7.42 mg
Dissolution of precipitate using HBr and HNO3, followed by pH adjustment using KOH
[Custom defined] Hydrobromic acid 680.81 mg
Nitric acid, without water, in 50% solution state {GLO}| market for | Alloc Def,
S 216.28 mg
Potassium hydroxide {GLO}| market for | Alloc Def, S 148.45 mg
Water, deionised, from tap water, at user {GLO}| market for | Alloc Def, S 1015.38 mg
Gold : α-cyclodextrin complex formation
[Custom defined] α-cyclodextrin 9.88 mg
Gold : α-cyclodextrin complex resuspension using sonication
Water, deionised, from tap water, at user {GLO}| market for | Alloc Def, S 5076.92 mg
Electricity, medium voltage {NPCC, US only}| market for | Alloc Def, S 4.21 kJ
Gold precipitation from gold : α-cyclodextrin complex
Sodium hydrogen sulfite {GLO}| market for | Alloc Def, S 138.95 mg
[Note: Sodium metabisulfite (Na2S2O5) was not available in the EcoInvent
inventory. Instead, we used sodium hydrogen sulfite (NaHSO3) in the LCA
models]
Dissolution of recovered gold in aqua regia
Hydrochloric acid, without water, in 30% solution state {RER}| hydrochloric
acid production, from the reaction of hydrogen with chlorine | Alloc Def, S 452.99 mg
Nitric acid, without water, in 50% solution state {RER}| nitric acid production,
product in 50% solution state | Alloc Def, S 180.35 mg
HNO3 boil-off , HCl addition and pH adjustment using KOH to obtain chloroauric acid for AuNP
synthesis from recovered gold
Hydrochloric acid, without water, in 30% solution state {RER}| hydrochloric
acid production, from the reaction of hydrogen with chlorine | Alloc Def, S 604.15 mg
Water, deionised, from tap water, at user {GLO}| market for | Alloc Def, S 10153.83 mg
Potassium hydroxide {GLO}| market for | Alloc Def, S 7.42 mg
Electricity, medium voltage {NPCC, US only}| market for | Alloc Def, S 0.07 MJ
UNCERTAINTY ANALYSIS IN LCA
LCA results typically involve correlated uncertainties. For example, the 90%-recycle and
no-recycle models use chemicals and processes from the life cycle inventories (such as gold,
water, electricity, etc.) that are common to both scenarios. In such cases, the uncertainty in the
LCA inventory for a chemical (say, gold) is common to all recycle scenarios, and is therefore
140
correlated. In the case of correlated uncertainties, differences in results may be statistically
significant, even if the error bars at the 95% confidence level overlap (Figure B4, left).
Therefore, we have chosen to represent uncertainty by comparing the actual Monte Carlo
simulations. As seen from the tabulated results in Figure B4 (right), of the 1000 runs performed
during Monte Carlo simulation, the majority show that recycling has lower environmental
burdens in the key impact categories (ecotoxicity, eutrophication, and metal depletion).
In Figure B5, B6 and B7, we show the percentage of the Monte Carlo simulations for different
recycle scenarios. For each of the impact categories, longer hatched bars indicate that for the majority of
Monte Carlo simulations, recycling has lower impact than the no-recycle scenario. Longer solid bars, on
Figure B 4 - (Left) The overlapping error bars for 95% confidence intervals should not be interpreted as
statistically insignificant differences, because these LCA models involve correlated uncertainties. (Right)
The majority of the Monte Carlo simulations showed that 90%-recycle scenario has lower impact than
no-recycle scenario in terms of metal depletion, toxicity and eutrophication.
141
the other hand, indicate that no-recycle scenarios have lower impact in those impact categories (as seen,
for example, in the Climate Change category).
Figure B 5 - Uncertainty analysis for 90% recycle scenario vs. no-recycle scenario.
142
Figure B 6 - Uncertainty analysis for 50% recycle scenario vs. no-recycle scenario.
143
Figure B 7 - Uncertainty analysis for 10% recycle scenario vs. no-recycle scenario.
144
Appendix C
Supplementary materials for Chapter 4
Bleeding from a Thousand Paper Cuts: Avoiding Dissipative Losses
of Critical Elements by Recycling Nanomaterial Waste Streams
Paramjeet Pati,1,2,3
Sean McGinnis,2,4
and Peter J. Vikesland1,2,3*
1Civil and Environmental Engineering, Virginia Tech
2Virginia Tech Institute of Critical Technology and Applied Science (ICTAS) Sustainable
Nanotechnology Center (VTSuN)
3Center for the Environmental Implications of Nanotechnology (CEINT), Duke University
4Department of Material Science and Engineering, Virginia Tech
*Corresponding author. Phone: (540) 231-3568, Email: [email protected]
Table C 1 - Recycling approaches for critical materials
Critical
material
Applications in
nanotechnology Recycling approaches
Indium
Photoelectrodes applications
for solar energy conversion 1
Optoelectric applications2
Biological imaging3
molecular-specific
spectroscopy,
Gas sensors (e.g., for CO,
NO2 4, NH3
5 etc.)
Pyrometallurgical recovery6
Anion exchange7
Air-classification of sputtering waste 8
Acid-resistant nanofiltration followed by
selective liquid−liquid extraction9
Neodymium
Nano-scale bacterial magnetic
particles for biotechnological
applications10
Non-contact11
and subtissue12
Gas phase extraction14, 15
Hydrogen decrepitation16, 17
Selective leaching from nitric acid medium
145
temperature sensing
photonic applications
(Infrared cameras, remote
controls)13
using functionalized ionic liquid
trioctylmethylammonium dioctyl diglycolamate 18
Hydrogenation disproportionation reaction19
Selective acid leaching followed solvent
extraction and precipitation20
Precipitation from electroplating wastewater21
Yttrium
Lasers and luminescent
materials22
Magneto-optical materials 23
Fuel cells24
Neuroprotective agent against
oxidative stress damage25
Acid leaching followed by, solvent extraction
and thermal reduction26
Extraction from chloride solution using an
extraction mixture comprised of 2-ethylhexyl
phosphonic acid mono-(2-ethylhexyl) ester,
Cyanex272, with kerosene as a diluent 27
Acid leaching from computer monitor scrap28
Acid leaching from spent fluorescent tubes
followed by precipitation using oxalic acid29
Dysprosium
Light emitting devices (e.g.,
ceramics30
and nano-
garnets31
)
Dopant in magnetic
nanoparticles32
Fingerprint detection33
Solid oxide fuel cells34
High strength corrosion
resistant ceramics and catalyst
supports35
Hydrometallurgical recovery from magnetic
waste sludge36
Selective volatilization followed by
carbochlorination37
Europium
Biological imaging38
Drug delivery39
Pathogen detection40
Extraction using quarternary ammonium based
ionic liquids41
Recovery from red lamp phosphor by selective
reduction of Eu(III) to Eu(II) followed by
precipitation of Eu as EuSO4, using
isopropanol as radical scavenger42
Terbium Molecular switches (based on Solid‐liquid extraction phosphoric acid medium
146
reversible chiral switching)43
Incorporation into glass-
ceramics for laser
applications44
Fluorescence imaging45
Phosphors46
using a bifunctional phosphinic acid resin
Tulsion CH‐96 47
Thorium
Ion-selective electrodes48, 49
Photoluminescence50
Recovery of Th from acid leaching solutions
using poly(styrene-co-maleic anhydride)
(PSMA) as adsorbent51
Extraction from sulfuric acid medium using 2-
ethylhexyl phosphoric acid mono 2-ethylhexyl
ester in kerosene52
Extraction from sulfuric acid medium using tri-
n-butyl phosphate (TBP)53
Extraction from nitrate medium using
diphenyl-N,N-
dimethylcarbamoylmethylphosphine oxide in
dichloromethane 54
Cerium
Antioxidant55, 56
Nanomedicine57
Fuel additive58
Acid leaching59
Leaching (using nitric acid liquor) followed by
selective extraction using ionic liquid
([C8mim]PF6)60
Gold
Pathogen detection61
Cancer diagnostics62
Drug delivery63
Cloud point extraction64
Selective complexation65
Magnetic recovery 66
Silver
Antimicrobial properties 67
Electrochemical detection68
Cloud point extraction69
Liquid-liquid phase separations70
Platinum
Fuel cells71
Catalysis72
Biosorption using yeast-based biomass
immobilized in polyvinyl alcohol cryogels73
Selective leaching from automobile catalyst
residue using chloride based leaching
solutions74
Selective recovery using thiourea modified
147
magnetic nanoparticles75
Palladium
Hydrogen sensors76
Fuel cells 77
Catalysis78
Smopex ® metal scavengers79
Bioreduction80, 81
Biosorption82
148
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155
Appendix D
Supplementary materials for Chapter 5
Seed Mediated Growth of Gold Nanoparticles at Room
Temperature: Mechanistic Investigation and Life Cycle Assessment
Weinan Leng, Paramjeet Pati, and Peter J. Vikesland
Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State
University, 418 Durham Hall, Blacksburg, VA 24060-0246
Table D 1 - Volumes (V) of nanopure water, HAuCl4, seed suspension, and trisodium citrate (Ctr) used in
the seed-mediated synthesis of the different sized nanoparticles.
AuNPs
intended
particle
size / nm
Vwater /
mL
VHAuCl4 a / mL
(c = 44.7 mM)
Vseed / mL
(d = 14 nm, c = 6.54
×1012
particles/ml)
Final seed
conc. (g/mL)
VCtr / mL
(c = 38.8
mM)
A 22.7 36.220 0.227 3.377 16.632 0.176
B 34.2 38.786 0.227 0.811 3.994 0.176
C 45.7 39.270 0.227 0.327 1.610 0.176
D 57.1 39.432 0.227 0.165 0.813 0.176
E 68.6 39.502 0.227 0.095 0.468 0.176
F 80.0 39.537 0.227 0.060 0.296 0.176
G 91.4 39.557 0.227 0.040 0.197 0.176
H 102.9 39.569 0.227 0.028 0.138 0.176
I 114.3 39.577 0.227 0.020 0.099 0.176 aFinal mass concentration for gold is 50 g/mL
156
Table D 2 - Inputs for 1 mg of the following custom-defined processes in SimaPro: a) Chloroauric acid,
b) Trosodium citrate, and c) AuNP ‘seeds’
[Custom defined] Chloroauric acid
Gold {US}| production | Alloc Def, S 0.72 mg
Hydrochloric acid, without water, in 30% solution state {RER}|
hydrochloric acid production, from the reaction of hydrogen with
chlorine | Alloc Def, S
0.13 mg
Chlorine, gaseous {RER}| sodium chloride electrolysis | Alloc Def,
S 0.39 mg
[Custom defined] Trisodium citrate
Citric acid {GLO}| market for | Alloc Def, S 0.51 mg
Soda ash, light, crystalline, heptahydrate {GLO}| market for | Alloc
Def, S 0.66 mg
[Custom defined] AuNP 'seeds'
[Custom defined] Chloroauric acid 1.73 mg
[Custom defined] Trisodium citrate 5.08 mg
Water, deionised, from tap water, at user {CH}| production | Alloc
Def, S 505.08 g
Tap water {CH}| market for | Alloc Def, S 30.00 g
Sodium hydroxide, without water, in 50% solution state {GLO}|
market for | Alloc Def, S 0.41 mg
Cleaning solvents
Hydrochloric acid, without water, in 30% solution state {RER}|
hydrochloric acid production, from the reaction of hydrogen with
chlorine | Alloc Def, S
1.81 mg
Nitric acid, without water, in 50% solution state {RER}| nitric acid
production, product in 50% solution state | Alloc Def, S 0.72 mg
[Stirring] Electricity, medium voltage {NPCC, US only}| market
for | Alloc Def, S 0.01 MJ
[Heating] Electricity, medium voltage {NPCC, US only}| market
for | Alloc Def, S 0.08 MJ
157
Table D 3 - Inputs for 1 mg of seed-mediated, citrate reduced AuNPs synthesized under boiling
conditions
[Custom defined] Chloroauric acid 1.94 mg
Water, deionised, from tap water, at user {CH}| production | Alloc
Def, S 444.13 g
Tap water {CH}| market for | Alloc Def, S 25.40 g
[Custom defined] AuNP 'seeds' 0.03 mg
Sodium hydroxide, without water, in 50% solution state {GLO}|
market for | Alloc Def, S 0.03 mg
[Custom defined] Trisodium citrate 0.09 mg
Cleaning solvents
Hydrochloric acid, without water, in 30% solution state {RER}|
hydrochloric acid production, from the reaction of hydrogen with
chlorine | Alloc Def, S
1.81 mg
Nitric acid, without water, in 50% solution state {RER}| nitric acid
production, product in 50% solution state | Alloc Def, S 0.72 mg
[Stirring] Electricity, medium voltage {NPCC, US only}| market for
| Alloc Def, S 0.08 kWh
[Heating] Electricity, medium voltage {NPCC, US only}| market for
| Alloc Def, S 0.97 kWh
Figure D 1 - Energy flows (cumulative energy demand) of 1 mg AuNP synthesis at 100 °C. (Flow lines
show individual contributions of different inputs.)
158
Table D 4 - Inputs for 1 mg of seed-mediated, citrate reduced AuNPs synthesized at room temperature
[Custom defined] Chloroauric acid 1.94 mg
Water, deionised, from tap water, at user {CH}| production | Alloc
Def, S 444.13 g
[Custom defined] AuNP 'seeds' 0.03 mg
Sodium hydroxide, without water, in 50% solution state {GLO}|
market for | Alloc Def, S 0.03 mg
[Custom defined] Trisodium citrate 0.09 mg
Cleaning solvents
Hydrochloric acid, without water, in 30% solution state {RER}|
hydrochloric acid production, from the reaction of hydrogen with
chlorine | Alloc Def, S
1.81 mg
Nitric acid, without water, in 50% solution state {RER}| nitric acid
production, product in 50% solution state | Alloc Def, S 0.72 mg
[Stirring] Electricity, medium voltage {NPCC, US only}| market for |
Alloc Def, S 0.76 kWh
Figure D 2 - Energy flows (cumulative energy demand) for 1 mg AuNP synthesis at room temperature.
(Flow lines show individual contributions of different inputs.)
159
0 5 10 15 20 25 30 35 40
3
4
5
6
7
y0 = 8.01
A1 = -3.4912
t1 = 2.60151
A2 = -1.80993
t2 = 92.43655
y = y0 + A
1exp(-x/t
1) + A
2exp(-x
0/t
2)
[Au]=1 mM
Na3Ctr / Au ratio
pH
valu
e
Figure D 3 - pH value at room temperature against the concentration ratio of Na3Ctr and AuIII
for a
fixed 1 mM AuIII
concentration.
160
FORMATION OF GOLD NANOPLATES AND NANORODS
Gold nanoplates and nanorods were observed in the seeded growth approach, especially
when seeds concentration was less than 1.6×1010
particles/mL (D – I). Under this condition, the
growth tends to rely on the individual seeds, and the interaction between seeds decreases. It is
different from the particles less than 50 nm, which includes two cluster formats in the early stage
and around 1.5 hour during seeds mediated growth. Figure S5 shows the growth process of 111
nm gold nanoparticles. We cannot see these phenomena neither from UV-vis spectra or change
of hydrodynamic size. The formation of rod or triangular-shaped nanoparticles is mostly due to
the rod or triangular-shaped seeds.2 Having the lowest surface energy of the (111) facet,
3 the
nanoparticles will be gradually grown by adding Au atoms or ions onto more energetically
0 1 2 3 4
0.6
0.7
0.8
0.9
1.0
E0 /
V
AuClx(OH)
4-x
Figure D 4 - The standard reduction potential (E0) for Au
III Au
0 for the gold solution species
AuClX(OH)4-X (x=0-4). E0 was calculated using the Nernst equation of ∆𝐺0 = −𝑛𝐹𝐸0, where Gibbs free
energy (G0) of AuClX(OH)4-X (x=0-4) was reported by Machesky et al.
1
161
favorable faces other than (111). This will result in the formation of nanoplates, same as the
nanorods and the hexagonally-arranged nanoparticles.2, 4
One the other hand, citrate ions and its
oxidation product – ACDC ions can also selectively adsorb on the (111) facets and hinder the
crystal growth in those directions. The average numbers of particles with different shapes were
counted and listed in Table D5.
Table D 5 - The percentage of nanoplates and nanorods in AuNP sample D – I.
Sample D E F G H I
n (# of nanoplates and nanorods) 21 14 15 32 16 17
N (# of particles counted) 216 148 156 343 126 213
Percentage / (100n/N)% 9.7 9.5 9.6 9.3 12.7 8.0
0 h 0.5 h 1 h 1.5 h 2.5 h 5 h
4 0 0 5 0 0 6 0 0 7 0 0 8 0 0
0 .0
0 .2
0 .4
0 .6
0 .8
t= 0
t= 0 .5 h t= 1 h
t= 1 .5 h
t= 2 .5 h
t= 5 h
Ab
so
rb
an
ce
W av elen g th / n m
0 2 4 6
2 0
4 0
6 0
8 0
1 0 0
Z-a
ve
dia
me
ter /
nm
T im e / h o u r
A
B C
Figure D 5 - Seed mediated growth with mixed solution of HAuCl4 (0.254 mM), Au seeds (3.3×109
particles/mL), and Na3Ctr (0.17 mM) at room temperature. (A) optical images, (B) absorption
spectra and (C) hydrodynamic diameter of growth solutions in different times.
162
1 1 0 1 0 0 1 0 0 0 1 0 0 0 0
s e e d s
In
te
ns
ity
(%
)
S iz e ( d /n m )
I
H
G
F
E
D
C
B
A
400 500 600 700 800
seeds
Abso
rban
ce (
arb. unit
s)
Wavelength / nm
Par
ticl
e si
ze
Par
ticl
e si
ze
BA
Figure D 6 - (A) Size distributions by intensity (DLS) and (B) absorption spectra of a set of seeded
growth prepared samples with increased size and shifted SPR.
163
200 250 300 350
0
1
2
Abso
rban
ce
Wavelength / nm
AuIII
trisodium citrate
mixture of AuIII
and trisodium citrate
theoretical addition of spectra of AuIII
and trisodium citrate
Figure D 7 - UV absorption spectra of [AuCl4]- (0.127mM, black solid line), Na3Ctr (0.088 mM, red line)
and the mixture of same volume of [AuCl4]- and Na3Ctr with final concentrations of 0.127 mM and 0.088
mM respectively (green line). Blue line is expected spectrum for the mixture based upon the combination
of the spectra for [AuCl4]- and Na3Ctr.
164
46 nm seed mediated AuNPs prepared at 100 oC. In brief, 0.818 mL seed suspension and 0.44
mL of 38.8 mM Na3Ctr were quickly added to a boiling solution of 100 mL of 0.254 mM
HAuCl4 under vigorous stirring. After a reaction period of 30 min, the AuNP suspension was
cooled down at room temperature under stirring.
200 250 300 350
0.0
0.2
0.4
0.6
0.8
1.0
Mixture of HCl and NaCl
Supernatant without AuNPs
Abso
rban
ce
Wavelength / nm
Figure D 8 - Comparison of UV absorbance between supernatant from a completely reacted Au solution
and a simulation mixture of HCl and NaCl. The final concentrations of HCl and NaCl are based on the
stoichiometry of equation 11.
165
Figure D 9 - TEM images of seed mediated 46 nm AuNPs produced at room temperature (A) and at 100 oC
(B).
Figure D 10- Cumulative energy demand (CED), marine eutrophication and water depletion for 1 mg
of 46 nm AuNP synthesis at 100 °C vs. room temperature. AuNP synthesis at room temperature has
lower environmental impacts than synthesis under boiling conditions
166
UNCERTAINTY ANALYSIS
LCA results typically involve correlated uncertainties. For example, some chemicals and
processes from the life cycle inventories (such as gold, water, electricity etc.) are common to
both synthesis methods - the room temperature AuNP synthesis and synthesis under boiling
conditions. In such cases, the uncertainty for a chemical (say, gold) is common to both models,
and therefore correlated5. In the case of correlated uncertainties, differences in results may be
statistically significant, even if the error bars for 95% confidence interval overlap. Therefore, we
have chosen to represent uncertainty in our LCA by comparing the actual Monte Carlo
simulations instead of comparing 95% confidence intervals. As mentioned in the main
manuscript, uncertainty analyses were performed using Monte-Carlo simulations for 1000 runs.
As shown in Figure S7, most of those 1000 simulations showed that across all impact categories,
AuNP synthesis at room temperature had lower impacts than previously reported methods that
involved boiling conditions.
167
Figure D 9 - The percentage of 1000 Monte Carlo simulations showing that across all impact
categories, most simulations show that the environmental impacts for room temperature AuNP
synthesis are lower than those for synthesis under boiling conditions.
168
REFERENCES
1. Machesky, M. L.; Andrade, W. O.; Rose, A. W., Adsorption of gold(III)-chloride and gold(I)-
thiosulfate anions by goethite. Geochimica et Cosmochimica Acta 1991, 55, (3), 769-76.
2. Xie, J.; Lee, J. Y.; Wang, D. I. C.; Ting, Y. P., Identification of active biomolecules in the high-
yield synthesis of single-crystalline gold nanoplates in algal solutions. Small 2007, 3, (4), 672-682.
3. Brown, S.; Sarikaya, M.; Johnson, E., A Genetic Analysis of Crystal Growth. J. Mol. Biol. 2000,
299, (3), 725-735.
4. Shao, Y.; Jin, Y.; Dong, S., Synthesis of gold nanoplates by aspartate reduction of gold chloride.
Chemical Communications (Cambridge, United Kingdom) 2004, (9), 1104-1105.
5. Goedkoop, M.; Schryver, A. D.; Oele, M.; Roest, D. D.; Vieira, M.; Durksz, S., SimaPro 7
Tutorial. PRé Consultants 2010.
169
Appendix E
Reprint Permission Letters
170
171
172
173
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